1 #include <petsc/private/tsimpl.h> /*I "petscts.h" I*/ 2 #include <petscdmshell.h> 3 #include <petscdmda.h> 4 #include <petscviewer.h> 5 #include <petscdraw.h> 6 7 /* Logging support */ 8 PetscClassId TS_CLASSID, DMTS_CLASSID; 9 PetscLogEvent TS_AdjointStep, TS_Step, TS_PseudoComputeTimeStep, TS_FunctionEval, TS_JacobianEval; 10 11 const char *const TSExactFinalTimeOptions[] = {"UNSPECIFIED","STEPOVER","INTERPOLATE","MATCHSTEP","TSExactFinalTimeOption","TS_EXACTFINALTIME_",0}; 12 13 struct _n_TSMonitorDrawCtx { 14 PetscViewer viewer; 15 Vec initialsolution; 16 PetscBool showinitial; 17 PetscInt howoften; /* when > 0 uses step % howoften, when negative only final solution plotted */ 18 PetscBool showtimestepandtime; 19 }; 20 21 /*@C 22 TSMonitorSetFromOptions - Sets a monitor function and viewer appropriate for the type indicated by the user 23 24 Collective on TS 25 26 Input Parameters: 27 + ts - TS object you wish to monitor 28 . name - the monitor type one is seeking 29 . help - message indicating what monitoring is done 30 . manual - manual page for the monitor 31 . monitor - the monitor function 32 - monitorsetup - a function that is called once ONLY if the user selected this monitor that may set additional features of the TS or PetscViewer objects 33 34 Level: developer 35 36 .seealso: PetscOptionsGetViewer(), PetscOptionsGetReal(), PetscOptionsHasName(), PetscOptionsGetString(), 37 PetscOptionsGetIntArray(), PetscOptionsGetRealArray(), PetscOptionsBool() 38 PetscOptionsInt(), PetscOptionsString(), PetscOptionsReal(), PetscOptionsBool(), 39 PetscOptionsName(), PetscOptionsBegin(), PetscOptionsEnd(), PetscOptionsHead(), 40 PetscOptionsStringArray(),PetscOptionsRealArray(), PetscOptionsScalar(), 41 PetscOptionsBoolGroupBegin(), PetscOptionsBoolGroup(), PetscOptionsBoolGroupEnd(), 42 PetscOptionsFList(), PetscOptionsEList() 43 @*/ 44 PetscErrorCode TSMonitorSetFromOptions(TS ts,const char name[],const char help[], const char manual[],PetscErrorCode (*monitor)(TS,PetscInt,PetscReal,Vec,PetscViewerAndFormat*),PetscErrorCode (*monitorsetup)(TS,PetscViewerAndFormat*)) 45 { 46 PetscErrorCode ierr; 47 PetscViewer viewer; 48 PetscViewerFormat format; 49 PetscBool flg; 50 51 PetscFunctionBegin; 52 ierr = PetscOptionsGetViewer(PetscObjectComm((PetscObject)ts),((PetscObject)ts)->prefix,name,&viewer,&format,&flg);CHKERRQ(ierr); 53 if (flg) { 54 PetscViewerAndFormat *vf; 55 ierr = PetscViewerAndFormatCreate(viewer,format,&vf);CHKERRQ(ierr); 56 ierr = PetscObjectDereference((PetscObject)viewer);CHKERRQ(ierr); 57 if (monitorsetup) { 58 ierr = (*monitorsetup)(ts,vf);CHKERRQ(ierr); 59 } 60 ierr = TSMonitorSet(ts,(PetscErrorCode (*)(TS,PetscInt,PetscReal,Vec,void*))monitor,vf,(PetscErrorCode (*)(void**))PetscViewerAndFormatDestroy);CHKERRQ(ierr); 61 } 62 PetscFunctionReturn(0); 63 } 64 65 /*@C 66 TSAdjointMonitorSensi - monitors the first lambda sensitivity 67 68 Level: intermediate 69 70 .keywords: TS, set, monitor 71 72 .seealso: TSAdjointMonitorSet() 73 @*/ 74 PetscErrorCode TSAdjointMonitorSensi(TS ts,PetscInt step,PetscReal ptime,Vec v,PetscInt numcost,Vec *lambda,Vec *mu,PetscViewerAndFormat *vf) 75 { 76 PetscErrorCode ierr; 77 PetscViewer viewer = vf->viewer; 78 79 PetscFunctionBegin; 80 PetscValidHeaderSpecific(viewer,PETSC_VIEWER_CLASSID,4); 81 ierr = PetscViewerPushFormat(viewer,vf->format);CHKERRQ(ierr); 82 ierr = VecView(lambda[0],viewer);CHKERRQ(ierr); 83 ierr = PetscViewerPopFormat(viewer);CHKERRQ(ierr); 84 PetscFunctionReturn(0); 85 } 86 87 /*@C 88 TSAdjointMonitorSetFromOptions - Sets a monitor function and viewer appropriate for the type indicated by the user 89 90 Collective on TS 91 92 Input Parameters: 93 + ts - TS object you wish to monitor 94 . name - the monitor type one is seeking 95 . help - message indicating what monitoring is done 96 . manual - manual page for the monitor 97 . monitor - the monitor function 98 - monitorsetup - a function that is called once ONLY if the user selected this monitor that may set additional features of the TS or PetscViewer objects 99 100 Level: developer 101 102 .seealso: PetscOptionsGetViewer(), PetscOptionsGetReal(), PetscOptionsHasName(), PetscOptionsGetString(), 103 PetscOptionsGetIntArray(), PetscOptionsGetRealArray(), PetscOptionsBool() 104 PetscOptionsInt(), PetscOptionsString(), PetscOptionsReal(), PetscOptionsBool(), 105 PetscOptionsName(), PetscOptionsBegin(), PetscOptionsEnd(), PetscOptionsHead(), 106 PetscOptionsStringArray(),PetscOptionsRealArray(), PetscOptionsScalar(), 107 PetscOptionsBoolGroupBegin(), PetscOptionsBoolGroup(), PetscOptionsBoolGroupEnd(), 108 PetscOptionsFList(), PetscOptionsEList() 109 @*/ 110 PetscErrorCode TSAdjointMonitorSetFromOptions(TS ts,const char name[],const char help[], const char manual[],PetscErrorCode (*monitor)(TS,PetscInt,PetscReal,Vec,PetscInt,Vec*,Vec*,PetscViewerAndFormat*),PetscErrorCode (*monitorsetup)(TS,PetscViewerAndFormat*)) 111 { 112 PetscErrorCode ierr; 113 PetscViewer viewer; 114 PetscViewerFormat format; 115 PetscBool flg; 116 117 PetscFunctionBegin; 118 ierr = PetscOptionsGetViewer(PetscObjectComm((PetscObject)ts),((PetscObject)ts)->prefix,name,&viewer,&format,&flg);CHKERRQ(ierr); 119 if (flg) { 120 PetscViewerAndFormat *vf; 121 ierr = PetscViewerAndFormatCreate(viewer,format,&vf);CHKERRQ(ierr); 122 ierr = PetscObjectDereference((PetscObject)viewer);CHKERRQ(ierr); 123 if (monitorsetup) { 124 ierr = (*monitorsetup)(ts,vf);CHKERRQ(ierr); 125 } 126 ierr = TSAdjointMonitorSet(ts,(PetscErrorCode (*)(TS,PetscInt,PetscReal,Vec,PetscInt,Vec*,Vec*,void*))monitor,vf,(PetscErrorCode (*)(void**))PetscViewerAndFormatDestroy);CHKERRQ(ierr); 127 } 128 PetscFunctionReturn(0); 129 } 130 131 static PetscErrorCode TSAdaptSetDefaultType(TSAdapt adapt,TSAdaptType default_type) 132 { 133 PetscErrorCode ierr; 134 135 PetscFunctionBegin; 136 PetscValidHeaderSpecific(adapt,TSADAPT_CLASSID,1); 137 PetscValidCharPointer(default_type,2); 138 if (!((PetscObject)adapt)->type_name) { 139 ierr = TSAdaptSetType(adapt,default_type);CHKERRQ(ierr); 140 } 141 PetscFunctionReturn(0); 142 } 143 144 /*@ 145 TSSetFromOptions - Sets various TS parameters from user options. 146 147 Collective on TS 148 149 Input Parameter: 150 . ts - the TS context obtained from TSCreate() 151 152 Options Database Keys: 153 + -ts_type <type> - TSEULER, TSBEULER, TSSUNDIALS, TSPSEUDO, TSCN, TSRK, TSTHETA, TSALPHA, TSGLLE, TSSSP, TSGLEE 154 . -ts_save_trajectory - checkpoint the solution at each time-step 155 . -ts_max_time <time> - maximum time to compute to 156 . -ts_max_steps <steps> - maximum number of time-steps to take 157 . -ts_init_time <time> - initial time to start computation 158 . -ts_final_time <time> - final time to compute to 159 . -ts_dt <dt> - initial time step 160 . -ts_exact_final_time <stepover,interpolate,matchstep> whether to stop at the exact given final time and how to compute the solution at that ti,e 161 . -ts_max_snes_failures <maxfailures> - Maximum number of nonlinear solve failures allowed 162 . -ts_max_reject <maxrejects> - Maximum number of step rejections before step fails 163 . -ts_error_if_step_fails <true,false> - Error if no step succeeds 164 . -ts_rtol <rtol> - relative tolerance for local truncation error 165 . -ts_atol <atol> Absolute tolerance for local truncation error 166 . -ts_adjoint_solve <yes,no> After solving the ODE/DAE solve the adjoint problem (requires -ts_save_trajectory) 167 . -ts_fd_color - Use finite differences with coloring to compute IJacobian 168 . -ts_monitor - print information at each timestep 169 . -ts_monitor_lg_solution - Monitor solution graphically 170 . -ts_monitor_lg_error - Monitor error graphically 171 . -ts_monitor_lg_timestep - Monitor timestep size graphically 172 . -ts_monitor_lg_timestep_log - Monitor log timestep size graphically 173 . -ts_monitor_lg_snes_iterations - Monitor number nonlinear iterations for each timestep graphically 174 . -ts_monitor_lg_ksp_iterations - Monitor number nonlinear iterations for each timestep graphically 175 . -ts_monitor_sp_eig - Monitor eigenvalues of linearized operator graphically 176 . -ts_monitor_draw_solution - Monitor solution graphically 177 . -ts_monitor_draw_solution_phase <xleft,yleft,xright,yright> - Monitor solution graphically with phase diagram, requires problem with exactly 2 degrees of freedom 178 . -ts_monitor_draw_error - Monitor error graphically, requires use to have provided TSSetSolutionFunction() 179 . -ts_monitor_solution [ascii binary draw][:filename][:viewerformat] - monitors the solution at each timestep 180 . -ts_monitor_solution_vtk <filename.vts,filename.vtu> - Save each time step to a binary file, use filename-%%03D.vts (filename-%%03D.vtu) 181 . -ts_monitor_envelope - determine maximum and minimum value of each component of the solution over the solution time 182 . -ts_adjoint_monitor - print information at each adjoint time step 183 - -ts_adjoint_monitor_draw_sensi - monitor the sensitivity of the first cost function wrt initial conditions (lambda[0]) graphically 184 185 Developer Note: We should unify all the -ts_monitor options in the way that -xxx_view has been unified 186 187 Level: beginner 188 189 .keywords: TS, timestep, set, options, database 190 191 .seealso: TSGetType() 192 @*/ 193 PetscErrorCode TSSetFromOptions(TS ts) 194 { 195 PetscBool opt,flg,tflg; 196 PetscErrorCode ierr; 197 char monfilename[PETSC_MAX_PATH_LEN]; 198 PetscReal time_step; 199 TSExactFinalTimeOption eftopt; 200 char dir[16]; 201 TSIFunction ifun; 202 const char *defaultType; 203 char typeName[256]; 204 205 PetscFunctionBegin; 206 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 207 208 ierr = TSRegisterAll();CHKERRQ(ierr); 209 ierr = TSGetIFunction(ts,NULL,&ifun,NULL);CHKERRQ(ierr); 210 211 ierr = PetscObjectOptionsBegin((PetscObject)ts);CHKERRQ(ierr); 212 if (((PetscObject)ts)->type_name) 213 defaultType = ((PetscObject)ts)->type_name; 214 else 215 defaultType = ifun ? TSBEULER : TSEULER; 216 ierr = PetscOptionsFList("-ts_type","TS method","TSSetType",TSList,defaultType,typeName,256,&opt);CHKERRQ(ierr); 217 if (opt) { 218 ierr = TSSetType(ts,typeName);CHKERRQ(ierr); 219 } else { 220 ierr = TSSetType(ts,defaultType);CHKERRQ(ierr); 221 } 222 223 /* Handle generic TS options */ 224 ierr = PetscOptionsReal("-ts_max_time","Maximum time to run to","TSSetMaxTime",ts->max_time,&ts->max_time,NULL);CHKERRQ(ierr); 225 ierr = PetscOptionsInt("-ts_max_steps","Maximum number of time steps","TSSetMaxSteps",ts->max_steps,&ts->max_steps,NULL);CHKERRQ(ierr); 226 ierr = PetscOptionsReal("-ts_init_time","Initial time","TSSetTime",ts->ptime,&ts->ptime,NULL);CHKERRQ(ierr); 227 ierr = PetscOptionsReal("-ts_final_time","Final time to run to","TSSetMaxTime",ts->max_time,&ts->max_time,NULL);CHKERRQ(ierr); 228 ierr = PetscOptionsReal("-ts_dt","Initial time step","TSSetTimeStep",ts->time_step,&time_step,&flg);CHKERRQ(ierr); 229 if (flg) {ierr = TSSetTimeStep(ts,time_step);CHKERRQ(ierr);} 230 ierr = PetscOptionsEnum("-ts_exact_final_time","Option for handling of final time step","TSSetExactFinalTime",TSExactFinalTimeOptions,(PetscEnum)ts->exact_final_time,(PetscEnum*)&eftopt,&flg);CHKERRQ(ierr); 231 if (flg) {ierr = TSSetExactFinalTime(ts,eftopt);CHKERRQ(ierr);} 232 ierr = PetscOptionsInt("-ts_max_snes_failures","Maximum number of nonlinear solve failures","TSSetMaxSNESFailures",ts->max_snes_failures,&ts->max_snes_failures,NULL);CHKERRQ(ierr); 233 ierr = PetscOptionsInt("-ts_max_reject","Maximum number of step rejections before step fails","TSSetMaxStepRejections",ts->max_reject,&ts->max_reject,NULL);CHKERRQ(ierr); 234 ierr = PetscOptionsBool("-ts_error_if_step_fails","Error if no step succeeds","TSSetErrorIfStepFails",ts->errorifstepfailed,&ts->errorifstepfailed,NULL);CHKERRQ(ierr); 235 ierr = PetscOptionsReal("-ts_rtol","Relative tolerance for local truncation error","TSSetTolerances",ts->rtol,&ts->rtol,NULL);CHKERRQ(ierr); 236 ierr = PetscOptionsReal("-ts_atol","Absolute tolerance for local truncation error","TSSetTolerances",ts->atol,&ts->atol,NULL);CHKERRQ(ierr); 237 238 #if defined(PETSC_HAVE_SAWS) 239 { 240 PetscBool set; 241 flg = PETSC_FALSE; 242 ierr = PetscOptionsBool("-ts_saws_block","Block for SAWs memory snooper at end of TSSolve","PetscObjectSAWsBlock",((PetscObject)ts)->amspublishblock,&flg,&set);CHKERRQ(ierr); 243 if (set) { 244 ierr = PetscObjectSAWsSetBlock((PetscObject)ts,flg);CHKERRQ(ierr); 245 } 246 } 247 #endif 248 249 /* Monitor options */ 250 ierr = TSMonitorSetFromOptions(ts,"-ts_monitor","Monitor time and timestep size","TSMonitorDefault",TSMonitorDefault,NULL);CHKERRQ(ierr); 251 ierr = TSMonitorSetFromOptions(ts,"-ts_monitor_solution","View the solution at each timestep","TSMonitorSolution",TSMonitorSolution,NULL);CHKERRQ(ierr); 252 ierr = TSAdjointMonitorSetFromOptions(ts,"-ts_adjoint_monitor","Monitor adjoint timestep size","TSAdjointMonitorDefault",TSAdjointMonitorDefault,NULL);CHKERRQ(ierr); 253 ierr = TSAdjointMonitorSetFromOptions(ts,"-ts_adjoint_monitor_sensi","Monitor sensitivity in the adjoint computation","TSAdjointMonitorSensi",TSAdjointMonitorSensi,NULL);CHKERRQ(ierr); 254 255 ierr = PetscOptionsString("-ts_monitor_python","Use Python function","TSMonitorSet",0,monfilename,PETSC_MAX_PATH_LEN,&flg);CHKERRQ(ierr); 256 if (flg) {ierr = PetscPythonMonitorSet((PetscObject)ts,monfilename);CHKERRQ(ierr);} 257 258 ierr = PetscOptionsName("-ts_monitor_lg_solution","Monitor solution graphically","TSMonitorLGSolution",&opt);CHKERRQ(ierr); 259 if (opt) { 260 TSMonitorLGCtx ctx; 261 PetscInt howoften = 1; 262 263 ierr = PetscOptionsInt("-ts_monitor_lg_solution","Monitor solution graphically","TSMonitorLGSolution",howoften,&howoften,NULL);CHKERRQ(ierr); 264 ierr = TSMonitorLGCtxCreate(PETSC_COMM_SELF,0,0,PETSC_DECIDE,PETSC_DECIDE,400,300,howoften,&ctx);CHKERRQ(ierr); 265 ierr = TSMonitorSet(ts,TSMonitorLGSolution,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxDestroy);CHKERRQ(ierr); 266 } 267 268 ierr = PetscOptionsName("-ts_monitor_lg_error","Monitor error graphically","TSMonitorLGError",&opt);CHKERRQ(ierr); 269 if (opt) { 270 TSMonitorLGCtx ctx; 271 PetscInt howoften = 1; 272 273 ierr = PetscOptionsInt("-ts_monitor_lg_error","Monitor error graphically","TSMonitorLGError",howoften,&howoften,NULL);CHKERRQ(ierr); 274 ierr = TSMonitorLGCtxCreate(PETSC_COMM_SELF,0,0,PETSC_DECIDE,PETSC_DECIDE,400,300,howoften,&ctx);CHKERRQ(ierr); 275 ierr = TSMonitorSet(ts,TSMonitorLGError,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxDestroy);CHKERRQ(ierr); 276 } 277 278 ierr = PetscOptionsName("-ts_monitor_lg_timestep","Monitor timestep size graphically","TSMonitorLGTimeStep",&opt);CHKERRQ(ierr); 279 if (opt) { 280 TSMonitorLGCtx ctx; 281 PetscInt howoften = 1; 282 283 ierr = PetscOptionsInt("-ts_monitor_lg_timestep","Monitor timestep size graphically","TSMonitorLGTimeStep",howoften,&howoften,NULL);CHKERRQ(ierr); 284 ierr = TSMonitorLGCtxCreate(PetscObjectComm((PetscObject)ts),NULL,NULL,PETSC_DECIDE,PETSC_DECIDE,400,300,howoften,&ctx);CHKERRQ(ierr); 285 ierr = TSMonitorSet(ts,TSMonitorLGTimeStep,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxDestroy);CHKERRQ(ierr); 286 } 287 ierr = PetscOptionsName("-ts_monitor_lg_timestep_log","Monitor log timestep size graphically","TSMonitorLGTimeStep",&opt);CHKERRQ(ierr); 288 if (opt) { 289 TSMonitorLGCtx ctx; 290 PetscInt howoften = 1; 291 292 ierr = PetscOptionsInt("-ts_monitor_lg_timestep_log","Monitor log timestep size graphically","TSMonitorLGTimeStep",howoften,&howoften,NULL);CHKERRQ(ierr); 293 ierr = TSMonitorLGCtxCreate(PetscObjectComm((PetscObject)ts),NULL,NULL,PETSC_DECIDE,PETSC_DECIDE,400,300,howoften,&ctx);CHKERRQ(ierr); 294 ierr = TSMonitorSet(ts,TSMonitorLGTimeStep,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxDestroy);CHKERRQ(ierr); 295 ctx->semilogy = PETSC_TRUE; 296 } 297 298 ierr = PetscOptionsName("-ts_monitor_lg_snes_iterations","Monitor number nonlinear iterations for each timestep graphically","TSMonitorLGSNESIterations",&opt);CHKERRQ(ierr); 299 if (opt) { 300 TSMonitorLGCtx ctx; 301 PetscInt howoften = 1; 302 303 ierr = PetscOptionsInt("-ts_monitor_lg_snes_iterations","Monitor number nonlinear iterations for each timestep graphically","TSMonitorLGSNESIterations",howoften,&howoften,NULL);CHKERRQ(ierr); 304 ierr = TSMonitorLGCtxCreate(PetscObjectComm((PetscObject)ts),NULL,NULL,PETSC_DECIDE,PETSC_DECIDE,400,300,howoften,&ctx);CHKERRQ(ierr); 305 ierr = TSMonitorSet(ts,TSMonitorLGSNESIterations,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxDestroy);CHKERRQ(ierr); 306 } 307 ierr = PetscOptionsName("-ts_monitor_lg_ksp_iterations","Monitor number nonlinear iterations for each timestep graphically","TSMonitorLGKSPIterations",&opt);CHKERRQ(ierr); 308 if (opt) { 309 TSMonitorLGCtx ctx; 310 PetscInt howoften = 1; 311 312 ierr = PetscOptionsInt("-ts_monitor_lg_ksp_iterations","Monitor number nonlinear iterations for each timestep graphically","TSMonitorLGKSPIterations",howoften,&howoften,NULL);CHKERRQ(ierr); 313 ierr = TSMonitorLGCtxCreate(PetscObjectComm((PetscObject)ts),NULL,NULL,PETSC_DECIDE,PETSC_DECIDE,400,300,howoften,&ctx);CHKERRQ(ierr); 314 ierr = TSMonitorSet(ts,TSMonitorLGKSPIterations,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxDestroy);CHKERRQ(ierr); 315 } 316 ierr = PetscOptionsName("-ts_monitor_sp_eig","Monitor eigenvalues of linearized operator graphically","TSMonitorSPEig",&opt);CHKERRQ(ierr); 317 if (opt) { 318 TSMonitorSPEigCtx ctx; 319 PetscInt howoften = 1; 320 321 ierr = PetscOptionsInt("-ts_monitor_sp_eig","Monitor eigenvalues of linearized operator graphically","TSMonitorSPEig",howoften,&howoften,NULL);CHKERRQ(ierr); 322 ierr = TSMonitorSPEigCtxCreate(PETSC_COMM_SELF,0,0,PETSC_DECIDE,PETSC_DECIDE,300,300,howoften,&ctx);CHKERRQ(ierr); 323 ierr = TSMonitorSet(ts,TSMonitorSPEig,ctx,(PetscErrorCode (*)(void**))TSMonitorSPEigCtxDestroy);CHKERRQ(ierr); 324 } 325 opt = PETSC_FALSE; 326 ierr = PetscOptionsName("-ts_monitor_draw_solution","Monitor solution graphically","TSMonitorDrawSolution",&opt);CHKERRQ(ierr); 327 if (opt) { 328 TSMonitorDrawCtx ctx; 329 PetscInt howoften = 1; 330 331 ierr = PetscOptionsInt("-ts_monitor_draw_solution","Monitor solution graphically","TSMonitorDrawSolution",howoften,&howoften,NULL);CHKERRQ(ierr); 332 ierr = TSMonitorDrawCtxCreate(PetscObjectComm((PetscObject)ts),0,0,PETSC_DECIDE,PETSC_DECIDE,300,300,howoften,&ctx);CHKERRQ(ierr); 333 ierr = TSMonitorSet(ts,TSMonitorDrawSolution,ctx,(PetscErrorCode (*)(void**))TSMonitorDrawCtxDestroy);CHKERRQ(ierr); 334 } 335 opt = PETSC_FALSE; 336 ierr = PetscOptionsName("-ts_adjoint_monitor_draw_sensi","Monitor adjoint sensitivities (lambda only) graphically","TSAdjointMonitorDrawSensi",&opt);CHKERRQ(ierr); 337 if (opt) { 338 TSMonitorDrawCtx ctx; 339 PetscInt howoften = 1; 340 341 ierr = PetscOptionsInt("-ts_adjoint_monitor_draw_sensi","Monitor adjoint sensitivities (lambda only) graphically","TSAdjointMonitorDrawSensi",howoften,&howoften,NULL);CHKERRQ(ierr); 342 ierr = TSMonitorDrawCtxCreate(PetscObjectComm((PetscObject)ts),0,0,PETSC_DECIDE,PETSC_DECIDE,300,300,howoften,&ctx);CHKERRQ(ierr); 343 ierr = TSAdjointMonitorSet(ts,TSAdjointMonitorDrawSensi,ctx,(PetscErrorCode (*)(void**))TSMonitorDrawCtxDestroy);CHKERRQ(ierr); 344 } 345 opt = PETSC_FALSE; 346 ierr = PetscOptionsName("-ts_monitor_draw_solution_phase","Monitor solution graphically","TSMonitorDrawSolutionPhase",&opt);CHKERRQ(ierr); 347 if (opt) { 348 TSMonitorDrawCtx ctx; 349 PetscReal bounds[4]; 350 PetscInt n = 4; 351 PetscDraw draw; 352 PetscDrawAxis axis; 353 354 ierr = PetscOptionsRealArray("-ts_monitor_draw_solution_phase","Monitor solution graphically","TSMonitorDrawSolutionPhase",bounds,&n,NULL);CHKERRQ(ierr); 355 if (n != 4) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONG,"Must provide bounding box of phase field"); 356 ierr = TSMonitorDrawCtxCreate(PetscObjectComm((PetscObject)ts),0,0,PETSC_DECIDE,PETSC_DECIDE,300,300,1,&ctx);CHKERRQ(ierr); 357 ierr = PetscViewerDrawGetDraw(ctx->viewer,0,&draw);CHKERRQ(ierr); 358 ierr = PetscViewerDrawGetDrawAxis(ctx->viewer,0,&axis);CHKERRQ(ierr); 359 ierr = PetscDrawAxisSetLimits(axis,bounds[0],bounds[2],bounds[1],bounds[3]);CHKERRQ(ierr); 360 ierr = PetscDrawAxisSetLabels(axis,"Phase Diagram","Variable 1","Variable 2");CHKERRQ(ierr); 361 ierr = TSMonitorSet(ts,TSMonitorDrawSolutionPhase,ctx,(PetscErrorCode (*)(void**))TSMonitorDrawCtxDestroy);CHKERRQ(ierr); 362 } 363 opt = PETSC_FALSE; 364 ierr = PetscOptionsName("-ts_monitor_draw_error","Monitor error graphically","TSMonitorDrawError",&opt);CHKERRQ(ierr); 365 if (opt) { 366 TSMonitorDrawCtx ctx; 367 PetscInt howoften = 1; 368 369 ierr = PetscOptionsInt("-ts_monitor_draw_error","Monitor error graphically","TSMonitorDrawError",howoften,&howoften,NULL);CHKERRQ(ierr); 370 ierr = TSMonitorDrawCtxCreate(PetscObjectComm((PetscObject)ts),0,0,PETSC_DECIDE,PETSC_DECIDE,300,300,howoften,&ctx);CHKERRQ(ierr); 371 ierr = TSMonitorSet(ts,TSMonitorDrawError,ctx,(PetscErrorCode (*)(void**))TSMonitorDrawCtxDestroy);CHKERRQ(ierr); 372 } 373 374 opt = PETSC_FALSE; 375 ierr = PetscOptionsString("-ts_monitor_solution_vtk","Save each time step to a binary file, use filename-%%03D.vts","TSMonitorSolutionVTK",0,monfilename,PETSC_MAX_PATH_LEN,&flg);CHKERRQ(ierr); 376 if (flg) { 377 const char *ptr,*ptr2; 378 char *filetemplate; 379 if (!monfilename[0]) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"-ts_monitor_solution_vtk requires a file template, e.g. filename-%%03D.vts"); 380 /* Do some cursory validation of the input. */ 381 ierr = PetscStrstr(monfilename,"%",(char**)&ptr);CHKERRQ(ierr); 382 if (!ptr) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"-ts_monitor_solution_vtk requires a file template, e.g. filename-%%03D.vts"); 383 for (ptr++; ptr && *ptr; ptr++) { 384 ierr = PetscStrchr("DdiouxX",*ptr,(char**)&ptr2);CHKERRQ(ierr); 385 if (!ptr2 && (*ptr < '0' || '9' < *ptr)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"Invalid file template argument to -ts_monitor_solution_vtk, should look like filename-%%03D.vts"); 386 if (ptr2) break; 387 } 388 ierr = PetscStrallocpy(monfilename,&filetemplate);CHKERRQ(ierr); 389 ierr = TSMonitorSet(ts,TSMonitorSolutionVTK,filetemplate,(PetscErrorCode (*)(void**))TSMonitorSolutionVTKDestroy);CHKERRQ(ierr); 390 } 391 392 ierr = PetscOptionsString("-ts_monitor_dmda_ray","Display a ray of the solution","None","y=0",dir,16,&flg);CHKERRQ(ierr); 393 if (flg) { 394 TSMonitorDMDARayCtx *rayctx; 395 int ray = 0; 396 DMDADirection ddir; 397 DM da; 398 PetscMPIInt rank; 399 400 if (dir[1] != '=') SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONG,"Unknown ray %s",dir); 401 if (dir[0] == 'x') ddir = DMDA_X; 402 else if (dir[0] == 'y') ddir = DMDA_Y; 403 else SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONG,"Unknown ray %s",dir); 404 sscanf(dir+2,"%d",&ray); 405 406 ierr = PetscInfo2(((PetscObject)ts),"Displaying DMDA ray %c = %D\n",dir[0],ray);CHKERRQ(ierr); 407 ierr = PetscNew(&rayctx);CHKERRQ(ierr); 408 ierr = TSGetDM(ts,&da);CHKERRQ(ierr); 409 ierr = DMDAGetRay(da,ddir,ray,&rayctx->ray,&rayctx->scatter);CHKERRQ(ierr); 410 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)ts),&rank);CHKERRQ(ierr); 411 if (!rank) { 412 ierr = PetscViewerDrawOpen(PETSC_COMM_SELF,0,0,0,0,600,300,&rayctx->viewer);CHKERRQ(ierr); 413 } 414 rayctx->lgctx = NULL; 415 ierr = TSMonitorSet(ts,TSMonitorDMDARay,rayctx,TSMonitorDMDARayDestroy);CHKERRQ(ierr); 416 } 417 ierr = PetscOptionsString("-ts_monitor_lg_dmda_ray","Display a ray of the solution","None","x=0",dir,16,&flg);CHKERRQ(ierr); 418 if (flg) { 419 TSMonitorDMDARayCtx *rayctx; 420 int ray = 0; 421 DMDADirection ddir; 422 DM da; 423 PetscInt howoften = 1; 424 425 if (dir[1] != '=') SETERRQ1(PetscObjectComm((PetscObject) ts), PETSC_ERR_ARG_WRONG, "Malformed ray %s", dir); 426 if (dir[0] == 'x') ddir = DMDA_X; 427 else if (dir[0] == 'y') ddir = DMDA_Y; 428 else SETERRQ1(PetscObjectComm((PetscObject) ts), PETSC_ERR_ARG_WRONG, "Unknown ray direction %s", dir); 429 sscanf(dir+2, "%d", &ray); 430 431 ierr = PetscInfo2(((PetscObject) ts),"Displaying LG DMDA ray %c = %D\n", dir[0], ray);CHKERRQ(ierr); 432 ierr = PetscNew(&rayctx);CHKERRQ(ierr); 433 ierr = TSGetDM(ts, &da);CHKERRQ(ierr); 434 ierr = DMDAGetRay(da, ddir, ray, &rayctx->ray, &rayctx->scatter);CHKERRQ(ierr); 435 ierr = TSMonitorLGCtxCreate(PETSC_COMM_SELF,0,0,PETSC_DECIDE,PETSC_DECIDE,600,400,howoften,&rayctx->lgctx);CHKERRQ(ierr); 436 ierr = TSMonitorSet(ts, TSMonitorLGDMDARay, rayctx, TSMonitorDMDARayDestroy);CHKERRQ(ierr); 437 } 438 439 ierr = PetscOptionsName("-ts_monitor_envelope","Monitor maximum and minimum value of each component of the solution","TSMonitorEnvelope",&opt);CHKERRQ(ierr); 440 if (opt) { 441 TSMonitorEnvelopeCtx ctx; 442 443 ierr = TSMonitorEnvelopeCtxCreate(ts,&ctx);CHKERRQ(ierr); 444 ierr = TSMonitorSet(ts,TSMonitorEnvelope,ctx,(PetscErrorCode (*)(void**))TSMonitorEnvelopeCtxDestroy);CHKERRQ(ierr); 445 } 446 447 flg = PETSC_FALSE; 448 ierr = PetscOptionsBool("-ts_fd_color", "Use finite differences with coloring to compute IJacobian", "TSComputeJacobianDefaultColor", flg, &flg, NULL);CHKERRQ(ierr); 449 if (flg) { 450 DM dm; 451 DMTS tdm; 452 453 ierr = TSGetDM(ts, &dm);CHKERRQ(ierr); 454 ierr = DMGetDMTS(dm, &tdm);CHKERRQ(ierr); 455 tdm->ijacobianctx = NULL; 456 ierr = TSSetIJacobian(ts, NULL, NULL, TSComputeIJacobianDefaultColor, 0);CHKERRQ(ierr); 457 ierr = PetscInfo(ts, "Setting default finite difference coloring Jacobian matrix\n");CHKERRQ(ierr); 458 } 459 460 /* Handle specific TS options */ 461 if (ts->ops->setfromoptions) { 462 ierr = (*ts->ops->setfromoptions)(PetscOptionsObject,ts);CHKERRQ(ierr); 463 } 464 465 /* Handle TSAdapt options */ 466 ierr = TSGetAdapt(ts,&ts->adapt);CHKERRQ(ierr); 467 ierr = TSAdaptSetDefaultType(ts->adapt,ts->default_adapt_type);CHKERRQ(ierr); 468 ierr = TSAdaptSetFromOptions(PetscOptionsObject,ts->adapt);CHKERRQ(ierr); 469 470 /* TS trajectory must be set after TS, since it may use some TS options above */ 471 tflg = ts->trajectory ? PETSC_TRUE : PETSC_FALSE; 472 ierr = PetscOptionsBool("-ts_save_trajectory","Save the solution at each timestep","TSSetSaveTrajectory",tflg,&tflg,NULL);CHKERRQ(ierr); 473 if (tflg) { 474 ierr = TSSetSaveTrajectory(ts);CHKERRQ(ierr); 475 } 476 tflg = ts->adjoint_solve ? PETSC_TRUE : PETSC_FALSE; 477 ierr = PetscOptionsBool("-ts_adjoint_solve","Solve the adjoint problem immediately after solving the forward problem","",tflg,&tflg,&flg);CHKERRQ(ierr); 478 if (flg) { 479 ierr = TSSetSaveTrajectory(ts);CHKERRQ(ierr); 480 ts->adjoint_solve = tflg; 481 } 482 483 /* process any options handlers added with PetscObjectAddOptionsHandler() */ 484 ierr = PetscObjectProcessOptionsHandlers(PetscOptionsObject,(PetscObject)ts);CHKERRQ(ierr); 485 ierr = PetscOptionsEnd();CHKERRQ(ierr); 486 487 if (ts->trajectory) { 488 ierr = TSTrajectorySetFromOptions(ts->trajectory,ts);CHKERRQ(ierr); 489 } 490 491 ierr = TSGetSNES(ts,&ts->snes);CHKERRQ(ierr); 492 if (ts->problem_type == TS_LINEAR) {ierr = SNESSetType(ts->snes,SNESKSPONLY);CHKERRQ(ierr);} 493 ierr = SNESSetFromOptions(ts->snes);CHKERRQ(ierr); 494 PetscFunctionReturn(0); 495 } 496 497 /*@ 498 TSGetTrajectory - Gets the trajectory from a TS if it exists 499 500 Collective on TS 501 502 Input Parameters: 503 . ts - the TS context obtained from TSCreate() 504 505 Output Parameters; 506 . tr - the TSTrajectory object, if it exists 507 508 Note: This routine should be called after all TS options have been set 509 510 Level: advanced 511 512 .seealso: TSGetTrajectory(), TSAdjointSolve(), TSTrajectory, TSTrajectoryCreate() 513 514 .keywords: TS, set, checkpoint, 515 @*/ 516 PetscErrorCode TSGetTrajectory(TS ts,TSTrajectory *tr) 517 { 518 PetscFunctionBegin; 519 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 520 *tr = ts->trajectory; 521 PetscFunctionReturn(0); 522 } 523 524 /*@ 525 TSSetSaveTrajectory - Causes the TS to save its solutions as it iterates forward in time in a TSTrajectory object 526 527 Collective on TS 528 529 Input Parameters: 530 . ts - the TS context obtained from TSCreate() 531 532 Options Database: 533 + -ts_save_trajectory - saves the trajectory to a file 534 - -ts_trajectory_type type 535 536 Note: This routine should be called after all TS options have been set 537 538 The TSTRAJECTORYVISUALIZATION files can be loaded into Python with $PETSC_DIR/bin/PetscBinaryIOTrajectory.py and 539 MATLAB with $PETSC_DIR/share/petsc/matlab/PetscReadBinaryTrajectory.m 540 541 Level: intermediate 542 543 .seealso: TSGetTrajectory(), TSAdjointSolve(), TSTrajectoryType, TSSetTrajectoryType() 544 545 .keywords: TS, set, checkpoint, 546 @*/ 547 PetscErrorCode TSSetSaveTrajectory(TS ts) 548 { 549 PetscErrorCode ierr; 550 551 PetscFunctionBegin; 552 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 553 if (!ts->trajectory) { 554 ierr = TSTrajectoryCreate(PetscObjectComm((PetscObject)ts),&ts->trajectory);CHKERRQ(ierr); 555 } 556 PetscFunctionReturn(0); 557 } 558 559 /*@ 560 TSComputeRHSJacobian - Computes the Jacobian matrix that has been 561 set with TSSetRHSJacobian(). 562 563 Collective on TS and Vec 564 565 Input Parameters: 566 + ts - the TS context 567 . t - current timestep 568 - U - input vector 569 570 Output Parameters: 571 + A - Jacobian matrix 572 . B - optional preconditioning matrix 573 - flag - flag indicating matrix structure 574 575 Notes: 576 Most users should not need to explicitly call this routine, as it 577 is used internally within the nonlinear solvers. 578 579 See KSPSetOperators() for important information about setting the 580 flag parameter. 581 582 Level: developer 583 584 .keywords: SNES, compute, Jacobian, matrix 585 586 .seealso: TSSetRHSJacobian(), KSPSetOperators() 587 @*/ 588 PetscErrorCode TSComputeRHSJacobian(TS ts,PetscReal t,Vec U,Mat A,Mat B) 589 { 590 PetscErrorCode ierr; 591 PetscObjectState Ustate; 592 PetscObjectId Uid; 593 DM dm; 594 DMTS tsdm; 595 TSRHSJacobian rhsjacobianfunc; 596 void *ctx; 597 TSIJacobian ijacobianfunc; 598 TSRHSFunction rhsfunction; 599 600 PetscFunctionBegin; 601 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 602 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 603 PetscCheckSameComm(ts,1,U,3); 604 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 605 ierr = DMGetDMTS(dm,&tsdm);CHKERRQ(ierr); 606 ierr = DMTSGetRHSJacobian(dm,&rhsjacobianfunc,&ctx);CHKERRQ(ierr); 607 ierr = DMTSGetIJacobian(dm,&ijacobianfunc,NULL);CHKERRQ(ierr); 608 ierr = DMTSGetRHSFunction(dm,&rhsfunction,&ctx);CHKERRQ(ierr); 609 ierr = PetscObjectStateGet((PetscObject)U,&Ustate);CHKERRQ(ierr); 610 ierr = PetscObjectGetId((PetscObject)U,&Uid);CHKERRQ(ierr); 611 if (ts->rhsjacobian.time == t && (ts->problem_type == TS_LINEAR || (ts->rhsjacobian.Xid == Uid && ts->rhsjacobian.Xstate == Ustate)) && (rhsfunction != TSComputeRHSFunctionLinear)) { 612 PetscFunctionReturn(0); 613 } 614 615 if (!rhsjacobianfunc && !ijacobianfunc) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"Must call TSSetRHSJacobian() and / or TSSetIJacobian()"); 616 617 if (ts->rhsjacobian.reuse) { 618 ierr = MatShift(A,-ts->rhsjacobian.shift);CHKERRQ(ierr); 619 ierr = MatScale(A,1./ts->rhsjacobian.scale);CHKERRQ(ierr); 620 if (B && A != B) { 621 ierr = MatShift(B,-ts->rhsjacobian.shift);CHKERRQ(ierr); 622 ierr = MatScale(B,1./ts->rhsjacobian.scale);CHKERRQ(ierr); 623 } 624 ts->rhsjacobian.shift = 0; 625 ts->rhsjacobian.scale = 1.; 626 } 627 628 if (rhsjacobianfunc) { 629 PetscBool missing; 630 ierr = PetscLogEventBegin(TS_JacobianEval,ts,U,A,B);CHKERRQ(ierr); 631 PetscStackPush("TS user Jacobian function"); 632 ierr = (*rhsjacobianfunc)(ts,t,U,A,B,ctx);CHKERRQ(ierr); 633 PetscStackPop; 634 ierr = PetscLogEventEnd(TS_JacobianEval,ts,U,A,B);CHKERRQ(ierr); 635 if (A) { 636 ierr = MatMissingDiagonal(A,&missing,NULL);CHKERRQ(ierr); 637 if (missing) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Amat passed to TSSetRHSJacobian() must have all diagonal entries set, if they are zero you must still set them with a zero value"); 638 } 639 if (B && B != A) { 640 ierr = MatMissingDiagonal(B,&missing,NULL);CHKERRQ(ierr); 641 if (missing) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Bmat passed to TSSetRHSJacobian() must have all diagonal entries set, if they are zero you must still set them with a zero value"); 642 } 643 } else { 644 ierr = MatZeroEntries(A);CHKERRQ(ierr); 645 if (A != B) {ierr = MatZeroEntries(B);CHKERRQ(ierr);} 646 } 647 ts->rhsjacobian.time = t; 648 ierr = PetscObjectGetId((PetscObject)U,&ts->rhsjacobian.Xid);CHKERRQ(ierr); 649 ierr = PetscObjectStateGet((PetscObject)U,&ts->rhsjacobian.Xstate);CHKERRQ(ierr); 650 PetscFunctionReturn(0); 651 } 652 653 /*@ 654 TSComputeRHSFunction - Evaluates the right-hand-side function. 655 656 Collective on TS and Vec 657 658 Input Parameters: 659 + ts - the TS context 660 . t - current time 661 - U - state vector 662 663 Output Parameter: 664 . y - right hand side 665 666 Note: 667 Most users should not need to explicitly call this routine, as it 668 is used internally within the nonlinear solvers. 669 670 Level: developer 671 672 .keywords: TS, compute 673 674 .seealso: TSSetRHSFunction(), TSComputeIFunction() 675 @*/ 676 PetscErrorCode TSComputeRHSFunction(TS ts,PetscReal t,Vec U,Vec y) 677 { 678 PetscErrorCode ierr; 679 TSRHSFunction rhsfunction; 680 TSIFunction ifunction; 681 void *ctx; 682 DM dm; 683 684 PetscFunctionBegin; 685 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 686 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 687 PetscValidHeaderSpecific(y,VEC_CLASSID,4); 688 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 689 ierr = DMTSGetRHSFunction(dm,&rhsfunction,&ctx);CHKERRQ(ierr); 690 ierr = DMTSGetIFunction(dm,&ifunction,NULL);CHKERRQ(ierr); 691 692 if (!rhsfunction && !ifunction) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"Must call TSSetRHSFunction() and / or TSSetIFunction()"); 693 694 ierr = PetscLogEventBegin(TS_FunctionEval,ts,U,y,0);CHKERRQ(ierr); 695 if (rhsfunction) { 696 PetscStackPush("TS user right-hand-side function"); 697 ierr = (*rhsfunction)(ts,t,U,y,ctx);CHKERRQ(ierr); 698 PetscStackPop; 699 } else { 700 ierr = VecZeroEntries(y);CHKERRQ(ierr); 701 } 702 703 ierr = PetscLogEventEnd(TS_FunctionEval,ts,U,y,0);CHKERRQ(ierr); 704 PetscFunctionReturn(0); 705 } 706 707 /*@ 708 TSComputeSolutionFunction - Evaluates the solution function. 709 710 Collective on TS and Vec 711 712 Input Parameters: 713 + ts - the TS context 714 - t - current time 715 716 Output Parameter: 717 . U - the solution 718 719 Note: 720 Most users should not need to explicitly call this routine, as it 721 is used internally within the nonlinear solvers. 722 723 Level: developer 724 725 .keywords: TS, compute 726 727 .seealso: TSSetSolutionFunction(), TSSetRHSFunction(), TSComputeIFunction() 728 @*/ 729 PetscErrorCode TSComputeSolutionFunction(TS ts,PetscReal t,Vec U) 730 { 731 PetscErrorCode ierr; 732 TSSolutionFunction solutionfunction; 733 void *ctx; 734 DM dm; 735 736 PetscFunctionBegin; 737 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 738 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 739 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 740 ierr = DMTSGetSolutionFunction(dm,&solutionfunction,&ctx);CHKERRQ(ierr); 741 742 if (solutionfunction) { 743 PetscStackPush("TS user solution function"); 744 ierr = (*solutionfunction)(ts,t,U,ctx);CHKERRQ(ierr); 745 PetscStackPop; 746 } 747 PetscFunctionReturn(0); 748 } 749 /*@ 750 TSComputeForcingFunction - Evaluates the forcing function. 751 752 Collective on TS and Vec 753 754 Input Parameters: 755 + ts - the TS context 756 - t - current time 757 758 Output Parameter: 759 . U - the function value 760 761 Note: 762 Most users should not need to explicitly call this routine, as it 763 is used internally within the nonlinear solvers. 764 765 Level: developer 766 767 .keywords: TS, compute 768 769 .seealso: TSSetSolutionFunction(), TSSetRHSFunction(), TSComputeIFunction() 770 @*/ 771 PetscErrorCode TSComputeForcingFunction(TS ts,PetscReal t,Vec U) 772 { 773 PetscErrorCode ierr, (*forcing)(TS,PetscReal,Vec,void*); 774 void *ctx; 775 DM dm; 776 777 PetscFunctionBegin; 778 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 779 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 780 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 781 ierr = DMTSGetForcingFunction(dm,&forcing,&ctx);CHKERRQ(ierr); 782 783 if (forcing) { 784 PetscStackPush("TS user forcing function"); 785 ierr = (*forcing)(ts,t,U,ctx);CHKERRQ(ierr); 786 PetscStackPop; 787 } 788 PetscFunctionReturn(0); 789 } 790 791 static PetscErrorCode TSGetRHSVec_Private(TS ts,Vec *Frhs) 792 { 793 Vec F; 794 PetscErrorCode ierr; 795 796 PetscFunctionBegin; 797 *Frhs = NULL; 798 ierr = TSGetIFunction(ts,&F,NULL,NULL);CHKERRQ(ierr); 799 if (!ts->Frhs) { 800 ierr = VecDuplicate(F,&ts->Frhs);CHKERRQ(ierr); 801 } 802 *Frhs = ts->Frhs; 803 PetscFunctionReturn(0); 804 } 805 806 static PetscErrorCode TSGetRHSMats_Private(TS ts,Mat *Arhs,Mat *Brhs) 807 { 808 Mat A,B; 809 PetscErrorCode ierr; 810 TSIJacobian ijacobian; 811 812 PetscFunctionBegin; 813 if (Arhs) *Arhs = NULL; 814 if (Brhs) *Brhs = NULL; 815 ierr = TSGetIJacobian(ts,&A,&B,&ijacobian,NULL);CHKERRQ(ierr); 816 if (Arhs) { 817 if (!ts->Arhs) { 818 if (ijacobian) { 819 ierr = MatDuplicate(A,MAT_DO_NOT_COPY_VALUES,&ts->Arhs);CHKERRQ(ierr); 820 } else { 821 ts->Arhs = A; 822 ierr = PetscObjectReference((PetscObject)A);CHKERRQ(ierr); 823 } 824 } else { 825 PetscBool flg; 826 ierr = SNESGetUseMatrixFree(ts->snes,NULL,&flg);CHKERRQ(ierr); 827 /* Handle case where user provided only RHSJacobian and used -snes_mf_operator */ 828 if (flg && !ijacobian && ts->Arhs == ts->Brhs){ 829 ierr = PetscObjectDereference((PetscObject)ts->Arhs);CHKERRQ(ierr); 830 ts->Arhs = A; 831 ierr = PetscObjectReference((PetscObject)A);CHKERRQ(ierr); 832 } 833 } 834 *Arhs = ts->Arhs; 835 } 836 if (Brhs) { 837 if (!ts->Brhs) { 838 if (A != B) { 839 if (ijacobian) { 840 ierr = MatDuplicate(B,MAT_DO_NOT_COPY_VALUES,&ts->Brhs);CHKERRQ(ierr); 841 } else { 842 ts->Brhs = B; 843 ierr = PetscObjectReference((PetscObject)B);CHKERRQ(ierr); 844 } 845 } else { 846 ierr = PetscObjectReference((PetscObject)ts->Arhs);CHKERRQ(ierr); 847 ts->Brhs = ts->Arhs; 848 } 849 } 850 *Brhs = ts->Brhs; 851 } 852 PetscFunctionReturn(0); 853 } 854 855 /*@ 856 TSComputeIFunction - Evaluates the DAE residual written in implicit form F(t,U,Udot)=0 857 858 Collective on TS and Vec 859 860 Input Parameters: 861 + ts - the TS context 862 . t - current time 863 . U - state vector 864 . Udot - time derivative of state vector 865 - imex - flag indicates if the method is IMEX so that the RHSFunction should be kept separate 866 867 Output Parameter: 868 . Y - right hand side 869 870 Note: 871 Most users should not need to explicitly call this routine, as it 872 is used internally within the nonlinear solvers. 873 874 If the user did did not write their equations in implicit form, this 875 function recasts them in implicit form. 876 877 Level: developer 878 879 .keywords: TS, compute 880 881 .seealso: TSSetIFunction(), TSComputeRHSFunction() 882 @*/ 883 PetscErrorCode TSComputeIFunction(TS ts,PetscReal t,Vec U,Vec Udot,Vec Y,PetscBool imex) 884 { 885 PetscErrorCode ierr; 886 TSIFunction ifunction; 887 TSRHSFunction rhsfunction; 888 void *ctx; 889 DM dm; 890 891 PetscFunctionBegin; 892 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 893 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 894 PetscValidHeaderSpecific(Udot,VEC_CLASSID,4); 895 PetscValidHeaderSpecific(Y,VEC_CLASSID,5); 896 897 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 898 ierr = DMTSGetIFunction(dm,&ifunction,&ctx);CHKERRQ(ierr); 899 ierr = DMTSGetRHSFunction(dm,&rhsfunction,NULL);CHKERRQ(ierr); 900 901 if (!rhsfunction && !ifunction) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"Must call TSSetRHSFunction() and / or TSSetIFunction()"); 902 903 ierr = PetscLogEventBegin(TS_FunctionEval,ts,U,Udot,Y);CHKERRQ(ierr); 904 if (ifunction) { 905 PetscStackPush("TS user implicit function"); 906 ierr = (*ifunction)(ts,t,U,Udot,Y,ctx);CHKERRQ(ierr); 907 PetscStackPop; 908 } 909 if (imex) { 910 if (!ifunction) { 911 ierr = VecCopy(Udot,Y);CHKERRQ(ierr); 912 } 913 } else if (rhsfunction) { 914 if (ifunction) { 915 Vec Frhs; 916 ierr = TSGetRHSVec_Private(ts,&Frhs);CHKERRQ(ierr); 917 ierr = TSComputeRHSFunction(ts,t,U,Frhs);CHKERRQ(ierr); 918 ierr = VecAXPY(Y,-1,Frhs);CHKERRQ(ierr); 919 } else { 920 ierr = TSComputeRHSFunction(ts,t,U,Y);CHKERRQ(ierr); 921 ierr = VecAYPX(Y,-1,Udot);CHKERRQ(ierr); 922 } 923 } 924 ierr = PetscLogEventEnd(TS_FunctionEval,ts,U,Udot,Y);CHKERRQ(ierr); 925 PetscFunctionReturn(0); 926 } 927 928 /*@ 929 TSComputeIJacobian - Evaluates the Jacobian of the DAE 930 931 Collective on TS and Vec 932 933 Input 934 Input Parameters: 935 + ts - the TS context 936 . t - current timestep 937 . U - state vector 938 . Udot - time derivative of state vector 939 . shift - shift to apply, see note below 940 - imex - flag indicates if the method is IMEX so that the RHSJacobian should be kept separate 941 942 Output Parameters: 943 + A - Jacobian matrix 944 - B - matrix from which the preconditioner is constructed; often the same as A 945 946 Notes: 947 If F(t,U,Udot)=0 is the DAE, the required Jacobian is 948 949 dF/dU + shift*dF/dUdot 950 951 Most users should not need to explicitly call this routine, as it 952 is used internally within the nonlinear solvers. 953 954 Level: developer 955 956 .keywords: TS, compute, Jacobian, matrix 957 958 .seealso: TSSetIJacobian() 959 @*/ 960 PetscErrorCode TSComputeIJacobian(TS ts,PetscReal t,Vec U,Vec Udot,PetscReal shift,Mat A,Mat B,PetscBool imex) 961 { 962 PetscErrorCode ierr; 963 TSIJacobian ijacobian; 964 TSRHSJacobian rhsjacobian; 965 DM dm; 966 void *ctx; 967 968 PetscFunctionBegin; 969 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 970 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 971 PetscValidHeaderSpecific(Udot,VEC_CLASSID,4); 972 PetscValidPointer(A,6); 973 PetscValidHeaderSpecific(A,MAT_CLASSID,6); 974 PetscValidPointer(B,7); 975 PetscValidHeaderSpecific(B,MAT_CLASSID,7); 976 977 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 978 ierr = DMTSGetIJacobian(dm,&ijacobian,&ctx);CHKERRQ(ierr); 979 ierr = DMTSGetRHSJacobian(dm,&rhsjacobian,NULL);CHKERRQ(ierr); 980 981 if (!rhsjacobian && !ijacobian) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"Must call TSSetRHSJacobian() and / or TSSetIJacobian()"); 982 983 ierr = PetscLogEventBegin(TS_JacobianEval,ts,U,A,B);CHKERRQ(ierr); 984 if (ijacobian) { 985 PetscBool missing; 986 PetscStackPush("TS user implicit Jacobian"); 987 ierr = (*ijacobian)(ts,t,U,Udot,shift,A,B,ctx);CHKERRQ(ierr); 988 PetscStackPop; 989 ierr = MatMissingDiagonal(A,&missing,NULL);CHKERRQ(ierr); 990 if (missing) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Amat passed to TSSetIJacobian() must have all diagonal entries set, if they are zero you must still set them with a zero value"); 991 if (B != A) { 992 ierr = MatMissingDiagonal(B,&missing,NULL);CHKERRQ(ierr); 993 if (missing) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Bmat passed to TSSetIJacobian() must have all diagonal entries set, if they are zero you must still set them with a zero value"); 994 } 995 } 996 if (imex) { 997 if (!ijacobian) { /* system was written as Udot = G(t,U) */ 998 PetscBool assembled; 999 ierr = MatZeroEntries(A);CHKERRQ(ierr); 1000 ierr = MatAssembled(A,&assembled);CHKERRQ(ierr); 1001 if (!assembled) { 1002 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1003 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1004 } 1005 ierr = MatShift(A,shift);CHKERRQ(ierr); 1006 if (A != B) { 1007 ierr = MatZeroEntries(B);CHKERRQ(ierr); 1008 ierr = MatAssembled(B,&assembled);CHKERRQ(ierr); 1009 if (!assembled) { 1010 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1011 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1012 } 1013 ierr = MatShift(B,shift);CHKERRQ(ierr); 1014 } 1015 } 1016 } else { 1017 Mat Arhs = NULL,Brhs = NULL; 1018 if (rhsjacobian) { 1019 ierr = TSGetRHSMats_Private(ts,&Arhs,&Brhs);CHKERRQ(ierr); 1020 ierr = TSComputeRHSJacobian(ts,t,U,Arhs,Brhs);CHKERRQ(ierr); 1021 } 1022 if (Arhs == A) { /* No IJacobian, so we only have the RHS matrix */ 1023 PetscBool flg; 1024 ts->rhsjacobian.scale = -1; 1025 ts->rhsjacobian.shift = shift; 1026 ierr = SNESGetUseMatrixFree(ts->snes,NULL,&flg);CHKERRQ(ierr); 1027 /* since -snes_mf_operator uses the full SNES function it does not need to be shifted or scaled here */ 1028 if (!flg) { 1029 ierr = MatScale(A,-1);CHKERRQ(ierr); 1030 ierr = MatShift(A,shift);CHKERRQ(ierr); 1031 } 1032 if (A != B) { 1033 ierr = MatScale(B,-1);CHKERRQ(ierr); 1034 ierr = MatShift(B,shift);CHKERRQ(ierr); 1035 } 1036 } else if (Arhs) { /* Both IJacobian and RHSJacobian */ 1037 MatStructure axpy = DIFFERENT_NONZERO_PATTERN; 1038 if (!ijacobian) { /* No IJacobian provided, but we have a separate RHS matrix */ 1039 ierr = MatZeroEntries(A);CHKERRQ(ierr); 1040 ierr = MatShift(A,shift);CHKERRQ(ierr); 1041 if (A != B) { 1042 ierr = MatZeroEntries(B);CHKERRQ(ierr); 1043 ierr = MatShift(B,shift);CHKERRQ(ierr); 1044 } 1045 } 1046 ierr = MatAXPY(A,-1,Arhs,axpy);CHKERRQ(ierr); 1047 if (A != B) { 1048 ierr = MatAXPY(B,-1,Brhs,axpy);CHKERRQ(ierr); 1049 } 1050 } 1051 } 1052 ierr = PetscLogEventEnd(TS_JacobianEval,ts,U,A,B);CHKERRQ(ierr); 1053 PetscFunctionReturn(0); 1054 } 1055 1056 /*@C 1057 TSSetRHSFunction - Sets the routine for evaluating the function, 1058 where U_t = G(t,u). 1059 1060 Logically Collective on TS 1061 1062 Input Parameters: 1063 + ts - the TS context obtained from TSCreate() 1064 . r - vector to put the computed right hand side (or NULL to have it created) 1065 . f - routine for evaluating the right-hand-side function 1066 - ctx - [optional] user-defined context for private data for the 1067 function evaluation routine (may be NULL) 1068 1069 Calling sequence of func: 1070 $ func (TS ts,PetscReal t,Vec u,Vec F,void *ctx); 1071 1072 + t - current timestep 1073 . u - input vector 1074 . F - function vector 1075 - ctx - [optional] user-defined function context 1076 1077 Level: beginner 1078 1079 Notes: You must call this function or TSSetIFunction() to define your ODE. You cannot use this function when solving a DAE. 1080 1081 .keywords: TS, timestep, set, right-hand-side, function 1082 1083 .seealso: TSSetRHSJacobian(), TSSetIJacobian(), TSSetIFunction() 1084 @*/ 1085 PetscErrorCode TSSetRHSFunction(TS ts,Vec r,PetscErrorCode (*f)(TS,PetscReal,Vec,Vec,void*),void *ctx) 1086 { 1087 PetscErrorCode ierr; 1088 SNES snes; 1089 Vec ralloc = NULL; 1090 DM dm; 1091 1092 PetscFunctionBegin; 1093 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1094 if (r) PetscValidHeaderSpecific(r,VEC_CLASSID,2); 1095 1096 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1097 ierr = DMTSSetRHSFunction(dm,f,ctx);CHKERRQ(ierr); 1098 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 1099 if (!r && !ts->dm && ts->vec_sol) { 1100 ierr = VecDuplicate(ts->vec_sol,&ralloc);CHKERRQ(ierr); 1101 r = ralloc; 1102 } 1103 ierr = SNESSetFunction(snes,r,SNESTSFormFunction,ts);CHKERRQ(ierr); 1104 ierr = VecDestroy(&ralloc);CHKERRQ(ierr); 1105 PetscFunctionReturn(0); 1106 } 1107 1108 /*@C 1109 TSSetSolutionFunction - Provide a function that computes the solution of the ODE or DAE 1110 1111 Logically Collective on TS 1112 1113 Input Parameters: 1114 + ts - the TS context obtained from TSCreate() 1115 . f - routine for evaluating the solution 1116 - ctx - [optional] user-defined context for private data for the 1117 function evaluation routine (may be NULL) 1118 1119 Calling sequence of func: 1120 $ func (TS ts,PetscReal t,Vec u,void *ctx); 1121 1122 + t - current timestep 1123 . u - output vector 1124 - ctx - [optional] user-defined function context 1125 1126 Notes: 1127 This routine is used for testing accuracy of time integration schemes when you already know the solution. 1128 If analytic solutions are not known for your system, consider using the Method of Manufactured Solutions to 1129 create closed-form solutions with non-physical forcing terms. 1130 1131 For low-dimensional problems solved in serial, such as small discrete systems, TSMonitorLGError() can be used to monitor the error history. 1132 1133 Level: beginner 1134 1135 .keywords: TS, timestep, set, right-hand-side, function 1136 1137 .seealso: TSSetRHSJacobian(), TSSetIJacobian(), TSComputeSolutionFunction(), TSSetForcingFunction() 1138 @*/ 1139 PetscErrorCode TSSetSolutionFunction(TS ts,PetscErrorCode (*f)(TS,PetscReal,Vec,void*),void *ctx) 1140 { 1141 PetscErrorCode ierr; 1142 DM dm; 1143 1144 PetscFunctionBegin; 1145 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1146 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1147 ierr = DMTSSetSolutionFunction(dm,f,ctx);CHKERRQ(ierr); 1148 PetscFunctionReturn(0); 1149 } 1150 1151 /*@C 1152 TSSetForcingFunction - Provide a function that computes a forcing term for a ODE or PDE 1153 1154 Logically Collective on TS 1155 1156 Input Parameters: 1157 + ts - the TS context obtained from TSCreate() 1158 . func - routine for evaluating the forcing function 1159 - ctx - [optional] user-defined context for private data for the 1160 function evaluation routine (may be NULL) 1161 1162 Calling sequence of func: 1163 $ func (TS ts,PetscReal t,Vec f,void *ctx); 1164 1165 + t - current timestep 1166 . f - output vector 1167 - ctx - [optional] user-defined function context 1168 1169 Notes: 1170 This routine is useful for testing accuracy of time integration schemes when using the Method of Manufactured Solutions to 1171 create closed-form solutions with a non-physical forcing term. It allows you to use the Method of Manufactored Solution without directly editing the 1172 definition of the problem you are solving and hence possibly introducing bugs. 1173 1174 This replaces the ODE F(u,u_t,t) = 0 the TS is solving with F(u,u_t,t) - func(t) = 0 1175 1176 This forcing function does not depend on the solution to the equations, it can only depend on spatial location, time, and possibly parameters, the 1177 parameters can be passed in the ctx variable. 1178 1179 For low-dimensional problems solved in serial, such as small discrete systems, TSMonitorLGError() can be used to monitor the error history. 1180 1181 Level: beginner 1182 1183 .keywords: TS, timestep, set, right-hand-side, function 1184 1185 .seealso: TSSetRHSJacobian(), TSSetIJacobian(), TSComputeSolutionFunction(), TSSetSolutionFunction() 1186 @*/ 1187 PetscErrorCode TSSetForcingFunction(TS ts,TSForcingFunction func,void *ctx) 1188 { 1189 PetscErrorCode ierr; 1190 DM dm; 1191 1192 PetscFunctionBegin; 1193 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1194 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1195 ierr = DMTSSetForcingFunction(dm,func,ctx);CHKERRQ(ierr); 1196 PetscFunctionReturn(0); 1197 } 1198 1199 /*@C 1200 TSSetRHSJacobian - Sets the function to compute the Jacobian of G, 1201 where U_t = G(U,t), as well as the location to store the matrix. 1202 1203 Logically Collective on TS 1204 1205 Input Parameters: 1206 + ts - the TS context obtained from TSCreate() 1207 . Amat - (approximate) Jacobian matrix 1208 . Pmat - matrix from which preconditioner is to be constructed (usually the same as Amat) 1209 . f - the Jacobian evaluation routine 1210 - ctx - [optional] user-defined context for private data for the 1211 Jacobian evaluation routine (may be NULL) 1212 1213 Calling sequence of f: 1214 $ func (TS ts,PetscReal t,Vec u,Mat A,Mat B,void *ctx); 1215 1216 + t - current timestep 1217 . u - input vector 1218 . Amat - (approximate) Jacobian matrix 1219 . Pmat - matrix from which preconditioner is to be constructed (usually the same as Amat) 1220 - ctx - [optional] user-defined context for matrix evaluation routine 1221 1222 Notes: 1223 You must set all the diagonal entries of the matrices, if they are zero you must still set them with a zero value 1224 1225 The TS solver may modify the nonzero structure and the entries of the matrices Amat and Pmat between the calls to f() 1226 You should not assume the values are the same in the next call to f() as you set them in the previous call. 1227 1228 Level: beginner 1229 1230 .keywords: TS, timestep, set, right-hand-side, Jacobian 1231 1232 .seealso: SNESComputeJacobianDefaultColor(), TSSetRHSFunction(), TSRHSJacobianSetReuse(), TSSetIJacobian() 1233 1234 @*/ 1235 PetscErrorCode TSSetRHSJacobian(TS ts,Mat Amat,Mat Pmat,TSRHSJacobian f,void *ctx) 1236 { 1237 PetscErrorCode ierr; 1238 SNES snes; 1239 DM dm; 1240 TSIJacobian ijacobian; 1241 1242 PetscFunctionBegin; 1243 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1244 if (Amat) PetscValidHeaderSpecific(Amat,MAT_CLASSID,2); 1245 if (Pmat) PetscValidHeaderSpecific(Pmat,MAT_CLASSID,3); 1246 if (Amat) PetscCheckSameComm(ts,1,Amat,2); 1247 if (Pmat) PetscCheckSameComm(ts,1,Pmat,3); 1248 1249 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1250 ierr = DMTSSetRHSJacobian(dm,f,ctx);CHKERRQ(ierr); 1251 if (f == TSComputeRHSJacobianConstant) { 1252 /* Handle this case automatically for the user; otherwise user should call themselves. */ 1253 ierr = TSRHSJacobianSetReuse(ts,PETSC_TRUE);CHKERRQ(ierr); 1254 } 1255 ierr = DMTSGetIJacobian(dm,&ijacobian,NULL);CHKERRQ(ierr); 1256 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 1257 if (!ijacobian) { 1258 ierr = SNESSetJacobian(snes,Amat,Pmat,SNESTSFormJacobian,ts);CHKERRQ(ierr); 1259 } 1260 if (Amat) { 1261 ierr = PetscObjectReference((PetscObject)Amat);CHKERRQ(ierr); 1262 ierr = MatDestroy(&ts->Arhs);CHKERRQ(ierr); 1263 ts->Arhs = Amat; 1264 } 1265 if (Pmat) { 1266 ierr = PetscObjectReference((PetscObject)Pmat);CHKERRQ(ierr); 1267 ierr = MatDestroy(&ts->Brhs);CHKERRQ(ierr); 1268 ts->Brhs = Pmat; 1269 } 1270 PetscFunctionReturn(0); 1271 } 1272 1273 /*@C 1274 TSSetIFunction - Set the function to compute F(t,U,U_t) where F() = 0 is the DAE to be solved. 1275 1276 Logically Collective on TS 1277 1278 Input Parameters: 1279 + ts - the TS context obtained from TSCreate() 1280 . r - vector to hold the residual (or NULL to have it created internally) 1281 . f - the function evaluation routine 1282 - ctx - user-defined context for private data for the function evaluation routine (may be NULL) 1283 1284 Calling sequence of f: 1285 $ f(TS ts,PetscReal t,Vec u,Vec u_t,Vec F,ctx); 1286 1287 + t - time at step/stage being solved 1288 . u - state vector 1289 . u_t - time derivative of state vector 1290 . F - function vector 1291 - ctx - [optional] user-defined context for matrix evaluation routine 1292 1293 Important: 1294 The user MUST call either this routine or TSSetRHSFunction() to define the ODE. When solving DAEs you must use this function. 1295 1296 Level: beginner 1297 1298 .keywords: TS, timestep, set, DAE, Jacobian 1299 1300 .seealso: TSSetRHSJacobian(), TSSetRHSFunction(), TSSetIJacobian() 1301 @*/ 1302 PetscErrorCode TSSetIFunction(TS ts,Vec r,TSIFunction f,void *ctx) 1303 { 1304 PetscErrorCode ierr; 1305 SNES snes; 1306 Vec ralloc = NULL; 1307 DM dm; 1308 1309 PetscFunctionBegin; 1310 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1311 if (r) PetscValidHeaderSpecific(r,VEC_CLASSID,2); 1312 1313 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1314 ierr = DMTSSetIFunction(dm,f,ctx);CHKERRQ(ierr); 1315 1316 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 1317 if (!r && !ts->dm && ts->vec_sol) { 1318 ierr = VecDuplicate(ts->vec_sol,&ralloc);CHKERRQ(ierr); 1319 r = ralloc; 1320 } 1321 ierr = SNESSetFunction(snes,r,SNESTSFormFunction,ts);CHKERRQ(ierr); 1322 ierr = VecDestroy(&ralloc);CHKERRQ(ierr); 1323 PetscFunctionReturn(0); 1324 } 1325 1326 /*@C 1327 TSGetIFunction - Returns the vector where the implicit residual is stored and the function/contex to compute it. 1328 1329 Not Collective 1330 1331 Input Parameter: 1332 . ts - the TS context 1333 1334 Output Parameter: 1335 + r - vector to hold residual (or NULL) 1336 . func - the function to compute residual (or NULL) 1337 - ctx - the function context (or NULL) 1338 1339 Level: advanced 1340 1341 .keywords: TS, nonlinear, get, function 1342 1343 .seealso: TSSetIFunction(), SNESGetFunction() 1344 @*/ 1345 PetscErrorCode TSGetIFunction(TS ts,Vec *r,TSIFunction *func,void **ctx) 1346 { 1347 PetscErrorCode ierr; 1348 SNES snes; 1349 DM dm; 1350 1351 PetscFunctionBegin; 1352 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1353 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 1354 ierr = SNESGetFunction(snes,r,NULL,NULL);CHKERRQ(ierr); 1355 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1356 ierr = DMTSGetIFunction(dm,func,ctx);CHKERRQ(ierr); 1357 PetscFunctionReturn(0); 1358 } 1359 1360 /*@C 1361 TSGetRHSFunction - Returns the vector where the right hand side is stored and the function/context to compute it. 1362 1363 Not Collective 1364 1365 Input Parameter: 1366 . ts - the TS context 1367 1368 Output Parameter: 1369 + r - vector to hold computed right hand side (or NULL) 1370 . func - the function to compute right hand side (or NULL) 1371 - ctx - the function context (or NULL) 1372 1373 Level: advanced 1374 1375 .keywords: TS, nonlinear, get, function 1376 1377 .seealso: TSSetRHSFunction(), SNESGetFunction() 1378 @*/ 1379 PetscErrorCode TSGetRHSFunction(TS ts,Vec *r,TSRHSFunction *func,void **ctx) 1380 { 1381 PetscErrorCode ierr; 1382 SNES snes; 1383 DM dm; 1384 1385 PetscFunctionBegin; 1386 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1387 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 1388 ierr = SNESGetFunction(snes,r,NULL,NULL);CHKERRQ(ierr); 1389 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1390 ierr = DMTSGetRHSFunction(dm,func,ctx);CHKERRQ(ierr); 1391 PetscFunctionReturn(0); 1392 } 1393 1394 /*@C 1395 TSSetIJacobian - Set the function to compute the matrix dF/dU + a*dF/dU_t where F(t,U,U_t) is the function 1396 provided with TSSetIFunction(). 1397 1398 Logically Collective on TS 1399 1400 Input Parameters: 1401 + ts - the TS context obtained from TSCreate() 1402 . Amat - (approximate) Jacobian matrix 1403 . Pmat - matrix used to compute preconditioner (usually the same as Amat) 1404 . f - the Jacobian evaluation routine 1405 - ctx - user-defined context for private data for the Jacobian evaluation routine (may be NULL) 1406 1407 Calling sequence of f: 1408 $ f(TS ts,PetscReal t,Vec U,Vec U_t,PetscReal a,Mat Amat,Mat Pmat,void *ctx); 1409 1410 + t - time at step/stage being solved 1411 . U - state vector 1412 . U_t - time derivative of state vector 1413 . a - shift 1414 . Amat - (approximate) Jacobian of F(t,U,W+a*U), equivalent to dF/dU + a*dF/dU_t 1415 . Pmat - matrix used for constructing preconditioner, usually the same as Amat 1416 - ctx - [optional] user-defined context for matrix evaluation routine 1417 1418 Notes: 1419 The matrices Amat and Pmat are exactly the matrices that are used by SNES for the nonlinear solve. 1420 1421 If you know the operator Amat has a null space you can use MatSetNullSpace() and MatSetTransposeNullSpace() to supply the null 1422 space to Amat and the KSP solvers will automatically use that null space as needed during the solution process. 1423 1424 The matrix dF/dU + a*dF/dU_t you provide turns out to be 1425 the Jacobian of F(t,U,W+a*U) where F(t,U,U_t) = 0 is the DAE to be solved. 1426 The time integrator internally approximates U_t by W+a*U where the positive "shift" 1427 a and vector W depend on the integration method, step size, and past states. For example with 1428 the backward Euler method a = 1/dt and W = -a*U(previous timestep) so 1429 W + a*U = a*(U - U(previous timestep)) = (U - U(previous timestep))/dt 1430 1431 You must set all the diagonal entries of the matrices, if they are zero you must still set them with a zero value 1432 1433 The TS solver may modify the nonzero structure and the entries of the matrices Amat and Pmat between the calls to f() 1434 You should not assume the values are the same in the next call to f() as you set them in the previous call. 1435 1436 Level: beginner 1437 1438 .keywords: TS, timestep, DAE, Jacobian 1439 1440 .seealso: TSSetIFunction(), TSSetRHSJacobian(), SNESComputeJacobianDefaultColor(), SNESComputeJacobianDefault(), TSSetRHSFunction() 1441 1442 @*/ 1443 PetscErrorCode TSSetIJacobian(TS ts,Mat Amat,Mat Pmat,TSIJacobian f,void *ctx) 1444 { 1445 PetscErrorCode ierr; 1446 SNES snes; 1447 DM dm; 1448 1449 PetscFunctionBegin; 1450 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1451 if (Amat) PetscValidHeaderSpecific(Amat,MAT_CLASSID,2); 1452 if (Pmat) PetscValidHeaderSpecific(Pmat,MAT_CLASSID,3); 1453 if (Amat) PetscCheckSameComm(ts,1,Amat,2); 1454 if (Pmat) PetscCheckSameComm(ts,1,Pmat,3); 1455 1456 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1457 ierr = DMTSSetIJacobian(dm,f,ctx);CHKERRQ(ierr); 1458 1459 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 1460 ierr = SNESSetJacobian(snes,Amat,Pmat,SNESTSFormJacobian,ts);CHKERRQ(ierr); 1461 PetscFunctionReturn(0); 1462 } 1463 1464 /*@ 1465 TSRHSJacobianSetReuse - restore RHS Jacobian before re-evaluating. Without this flag, TS will change the sign and 1466 shift the RHS Jacobian for a finite-time-step implicit solve, in which case the user function will need to recompute 1467 the entire Jacobian. The reuse flag must be set if the evaluation function will assume that the matrix entries have 1468 not been changed by the TS. 1469 1470 Logically Collective 1471 1472 Input Arguments: 1473 + ts - TS context obtained from TSCreate() 1474 - reuse - PETSC_TRUE if the RHS Jacobian 1475 1476 Level: intermediate 1477 1478 .seealso: TSSetRHSJacobian(), TSComputeRHSJacobianConstant() 1479 @*/ 1480 PetscErrorCode TSRHSJacobianSetReuse(TS ts,PetscBool reuse) 1481 { 1482 PetscFunctionBegin; 1483 ts->rhsjacobian.reuse = reuse; 1484 PetscFunctionReturn(0); 1485 } 1486 1487 /*@C 1488 TSSetI2Function - Set the function to compute F(t,U,U_t,U_tt) where F = 0 is the DAE to be solved. 1489 1490 Logically Collective on TS 1491 1492 Input Parameters: 1493 + ts - the TS context obtained from TSCreate() 1494 . F - vector to hold the residual (or NULL to have it created internally) 1495 . fun - the function evaluation routine 1496 - ctx - user-defined context for private data for the function evaluation routine (may be NULL) 1497 1498 Calling sequence of fun: 1499 $ fun(TS ts,PetscReal t,Vec U,Vec U_t,Vec U_tt,Vec F,ctx); 1500 1501 + t - time at step/stage being solved 1502 . U - state vector 1503 . U_t - time derivative of state vector 1504 . U_tt - second time derivative of state vector 1505 . F - function vector 1506 - ctx - [optional] user-defined context for matrix evaluation routine (may be NULL) 1507 1508 Level: beginner 1509 1510 .keywords: TS, timestep, set, ODE, DAE, Function 1511 1512 .seealso: TSSetI2Jacobian() 1513 @*/ 1514 PetscErrorCode TSSetI2Function(TS ts,Vec F,TSI2Function fun,void *ctx) 1515 { 1516 DM dm; 1517 PetscErrorCode ierr; 1518 1519 PetscFunctionBegin; 1520 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1521 if (F) PetscValidHeaderSpecific(F,VEC_CLASSID,2); 1522 ierr = TSSetIFunction(ts,F,NULL,NULL);CHKERRQ(ierr); 1523 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1524 ierr = DMTSSetI2Function(dm,fun,ctx);CHKERRQ(ierr); 1525 PetscFunctionReturn(0); 1526 } 1527 1528 /*@C 1529 TSGetI2Function - Returns the vector where the implicit residual is stored and the function/contex to compute it. 1530 1531 Not Collective 1532 1533 Input Parameter: 1534 . ts - the TS context 1535 1536 Output Parameter: 1537 + r - vector to hold residual (or NULL) 1538 . fun - the function to compute residual (or NULL) 1539 - ctx - the function context (or NULL) 1540 1541 Level: advanced 1542 1543 .keywords: TS, nonlinear, get, function 1544 1545 .seealso: TSSetI2Function(), SNESGetFunction() 1546 @*/ 1547 PetscErrorCode TSGetI2Function(TS ts,Vec *r,TSI2Function *fun,void **ctx) 1548 { 1549 PetscErrorCode ierr; 1550 SNES snes; 1551 DM dm; 1552 1553 PetscFunctionBegin; 1554 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1555 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 1556 ierr = SNESGetFunction(snes,r,NULL,NULL);CHKERRQ(ierr); 1557 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1558 ierr = DMTSGetI2Function(dm,fun,ctx);CHKERRQ(ierr); 1559 PetscFunctionReturn(0); 1560 } 1561 1562 /*@C 1563 TSSetI2Jacobian - Set the function to compute the matrix dF/dU + v*dF/dU_t + a*dF/dU_tt 1564 where F(t,U,U_t,U_tt) is the function you provided with TSSetI2Function(). 1565 1566 Logically Collective on TS 1567 1568 Input Parameters: 1569 + ts - the TS context obtained from TSCreate() 1570 . J - Jacobian matrix 1571 . P - preconditioning matrix for J (may be same as J) 1572 . jac - the Jacobian evaluation routine 1573 - ctx - user-defined context for private data for the Jacobian evaluation routine (may be NULL) 1574 1575 Calling sequence of jac: 1576 $ jac(TS ts,PetscReal t,Vec U,Vec U_t,Vec U_tt,PetscReal v,PetscReal a,Mat J,Mat P,void *ctx); 1577 1578 + t - time at step/stage being solved 1579 . U - state vector 1580 . U_t - time derivative of state vector 1581 . U_tt - second time derivative of state vector 1582 . v - shift for U_t 1583 . a - shift for U_tt 1584 . J - Jacobian of G(U) = F(t,U,W+v*U,W'+a*U), equivalent to dF/dU + v*dF/dU_t + a*dF/dU_tt 1585 . P - preconditioning matrix for J, may be same as J 1586 - ctx - [optional] user-defined context for matrix evaluation routine 1587 1588 Notes: 1589 The matrices J and P are exactly the matrices that are used by SNES for the nonlinear solve. 1590 1591 The matrix dF/dU + v*dF/dU_t + a*dF/dU_tt you provide turns out to be 1592 the Jacobian of G(U) = F(t,U,W+v*U,W'+a*U) where F(t,U,U_t,U_tt) = 0 is the DAE to be solved. 1593 The time integrator internally approximates U_t by W+v*U and U_tt by W'+a*U where the positive "shift" 1594 parameters 'v' and 'a' and vectors W, W' depend on the integration method, step size, and past states. 1595 1596 Level: beginner 1597 1598 .keywords: TS, timestep, set, ODE, DAE, Jacobian 1599 1600 .seealso: TSSetI2Function() 1601 @*/ 1602 PetscErrorCode TSSetI2Jacobian(TS ts,Mat J,Mat P,TSI2Jacobian jac,void *ctx) 1603 { 1604 DM dm; 1605 PetscErrorCode ierr; 1606 1607 PetscFunctionBegin; 1608 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1609 if (J) PetscValidHeaderSpecific(J,MAT_CLASSID,2); 1610 if (P) PetscValidHeaderSpecific(P,MAT_CLASSID,3); 1611 ierr = TSSetIJacobian(ts,J,P,NULL,NULL);CHKERRQ(ierr); 1612 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1613 ierr = DMTSSetI2Jacobian(dm,jac,ctx);CHKERRQ(ierr); 1614 PetscFunctionReturn(0); 1615 } 1616 1617 /*@C 1618 TSGetI2Jacobian - Returns the implicit Jacobian at the present timestep. 1619 1620 Not Collective, but parallel objects are returned if TS is parallel 1621 1622 Input Parameter: 1623 . ts - The TS context obtained from TSCreate() 1624 1625 Output Parameters: 1626 + J - The (approximate) Jacobian of F(t,U,U_t,U_tt) 1627 . P - The matrix from which the preconditioner is constructed, often the same as J 1628 . jac - The function to compute the Jacobian matrices 1629 - ctx - User-defined context for Jacobian evaluation routine 1630 1631 Notes: You can pass in NULL for any return argument you do not need. 1632 1633 Level: advanced 1634 1635 .seealso: TSGetTimeStep(), TSGetMatrices(), TSGetTime(), TSGetStepNumber() 1636 1637 .keywords: TS, timestep, get, matrix, Jacobian 1638 @*/ 1639 PetscErrorCode TSGetI2Jacobian(TS ts,Mat *J,Mat *P,TSI2Jacobian *jac,void **ctx) 1640 { 1641 PetscErrorCode ierr; 1642 SNES snes; 1643 DM dm; 1644 1645 PetscFunctionBegin; 1646 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 1647 ierr = SNESSetUpMatrices(snes);CHKERRQ(ierr); 1648 ierr = SNESGetJacobian(snes,J,P,NULL,NULL);CHKERRQ(ierr); 1649 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1650 ierr = DMTSGetI2Jacobian(dm,jac,ctx);CHKERRQ(ierr); 1651 PetscFunctionReturn(0); 1652 } 1653 1654 /*@ 1655 TSComputeI2Function - Evaluates the DAE residual written in implicit form F(t,U,U_t,U_tt) = 0 1656 1657 Collective on TS and Vec 1658 1659 Input Parameters: 1660 + ts - the TS context 1661 . t - current time 1662 . U - state vector 1663 . V - time derivative of state vector (U_t) 1664 - A - second time derivative of state vector (U_tt) 1665 1666 Output Parameter: 1667 . F - the residual vector 1668 1669 Note: 1670 Most users should not need to explicitly call this routine, as it 1671 is used internally within the nonlinear solvers. 1672 1673 Level: developer 1674 1675 .keywords: TS, compute, function, vector 1676 1677 .seealso: TSSetI2Function() 1678 @*/ 1679 PetscErrorCode TSComputeI2Function(TS ts,PetscReal t,Vec U,Vec V,Vec A,Vec F) 1680 { 1681 DM dm; 1682 TSI2Function I2Function; 1683 void *ctx; 1684 TSRHSFunction rhsfunction; 1685 PetscErrorCode ierr; 1686 1687 PetscFunctionBegin; 1688 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1689 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 1690 PetscValidHeaderSpecific(V,VEC_CLASSID,4); 1691 PetscValidHeaderSpecific(A,VEC_CLASSID,5); 1692 PetscValidHeaderSpecific(F,VEC_CLASSID,6); 1693 1694 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1695 ierr = DMTSGetI2Function(dm,&I2Function,&ctx);CHKERRQ(ierr); 1696 ierr = DMTSGetRHSFunction(dm,&rhsfunction,NULL);CHKERRQ(ierr); 1697 1698 if (!I2Function) { 1699 ierr = TSComputeIFunction(ts,t,U,A,F,PETSC_FALSE);CHKERRQ(ierr); 1700 PetscFunctionReturn(0); 1701 } 1702 1703 ierr = PetscLogEventBegin(TS_FunctionEval,ts,U,V,F);CHKERRQ(ierr); 1704 1705 PetscStackPush("TS user implicit function"); 1706 ierr = I2Function(ts,t,U,V,A,F,ctx);CHKERRQ(ierr); 1707 PetscStackPop; 1708 1709 if (rhsfunction) { 1710 Vec Frhs; 1711 ierr = TSGetRHSVec_Private(ts,&Frhs);CHKERRQ(ierr); 1712 ierr = TSComputeRHSFunction(ts,t,U,Frhs);CHKERRQ(ierr); 1713 ierr = VecAXPY(F,-1,Frhs);CHKERRQ(ierr); 1714 } 1715 1716 ierr = PetscLogEventEnd(TS_FunctionEval,ts,U,V,F);CHKERRQ(ierr); 1717 PetscFunctionReturn(0); 1718 } 1719 1720 /*@ 1721 TSComputeI2Jacobian - Evaluates the Jacobian of the DAE 1722 1723 Collective on TS and Vec 1724 1725 Input Parameters: 1726 + ts - the TS context 1727 . t - current timestep 1728 . U - state vector 1729 . V - time derivative of state vector 1730 . A - second time derivative of state vector 1731 . shiftV - shift to apply, see note below 1732 - shiftA - shift to apply, see note below 1733 1734 Output Parameters: 1735 + J - Jacobian matrix 1736 - P - optional preconditioning matrix 1737 1738 Notes: 1739 If F(t,U,V,A)=0 is the DAE, the required Jacobian is 1740 1741 dF/dU + shiftV*dF/dV + shiftA*dF/dA 1742 1743 Most users should not need to explicitly call this routine, as it 1744 is used internally within the nonlinear solvers. 1745 1746 Level: developer 1747 1748 .keywords: TS, compute, Jacobian, matrix 1749 1750 .seealso: TSSetI2Jacobian() 1751 @*/ 1752 PetscErrorCode TSComputeI2Jacobian(TS ts,PetscReal t,Vec U,Vec V,Vec A,PetscReal shiftV,PetscReal shiftA,Mat J,Mat P) 1753 { 1754 DM dm; 1755 TSI2Jacobian I2Jacobian; 1756 void *ctx; 1757 TSRHSJacobian rhsjacobian; 1758 PetscErrorCode ierr; 1759 1760 PetscFunctionBegin; 1761 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1762 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 1763 PetscValidHeaderSpecific(V,VEC_CLASSID,4); 1764 PetscValidHeaderSpecific(A,VEC_CLASSID,5); 1765 PetscValidHeaderSpecific(J,MAT_CLASSID,8); 1766 PetscValidHeaderSpecific(P,MAT_CLASSID,9); 1767 1768 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1769 ierr = DMTSGetI2Jacobian(dm,&I2Jacobian,&ctx);CHKERRQ(ierr); 1770 ierr = DMTSGetRHSJacobian(dm,&rhsjacobian,NULL);CHKERRQ(ierr); 1771 1772 if (!I2Jacobian) { 1773 ierr = TSComputeIJacobian(ts,t,U,A,shiftA,J,P,PETSC_FALSE);CHKERRQ(ierr); 1774 PetscFunctionReturn(0); 1775 } 1776 1777 ierr = PetscLogEventBegin(TS_JacobianEval,ts,U,J,P);CHKERRQ(ierr); 1778 1779 PetscStackPush("TS user implicit Jacobian"); 1780 ierr = I2Jacobian(ts,t,U,V,A,shiftV,shiftA,J,P,ctx);CHKERRQ(ierr); 1781 PetscStackPop; 1782 1783 if (rhsjacobian) { 1784 Mat Jrhs,Prhs; MatStructure axpy = DIFFERENT_NONZERO_PATTERN; 1785 ierr = TSGetRHSMats_Private(ts,&Jrhs,&Prhs);CHKERRQ(ierr); 1786 ierr = TSComputeRHSJacobian(ts,t,U,Jrhs,Prhs);CHKERRQ(ierr); 1787 ierr = MatAXPY(J,-1,Jrhs,axpy);CHKERRQ(ierr); 1788 if (P != J) {ierr = MatAXPY(P,-1,Prhs,axpy);CHKERRQ(ierr);} 1789 } 1790 1791 ierr = PetscLogEventEnd(TS_JacobianEval,ts,U,J,P);CHKERRQ(ierr); 1792 PetscFunctionReturn(0); 1793 } 1794 1795 /*@ 1796 TS2SetSolution - Sets the initial solution and time derivative vectors 1797 for use by the TS routines handling second order equations. 1798 1799 Logically Collective on TS and Vec 1800 1801 Input Parameters: 1802 + ts - the TS context obtained from TSCreate() 1803 . u - the solution vector 1804 - v - the time derivative vector 1805 1806 Level: beginner 1807 1808 .keywords: TS, timestep, set, solution, initial conditions 1809 @*/ 1810 PetscErrorCode TS2SetSolution(TS ts,Vec u,Vec v) 1811 { 1812 PetscErrorCode ierr; 1813 1814 PetscFunctionBegin; 1815 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1816 PetscValidHeaderSpecific(u,VEC_CLASSID,2); 1817 PetscValidHeaderSpecific(v,VEC_CLASSID,3); 1818 ierr = TSSetSolution(ts,u);CHKERRQ(ierr); 1819 ierr = PetscObjectReference((PetscObject)v);CHKERRQ(ierr); 1820 ierr = VecDestroy(&ts->vec_dot);CHKERRQ(ierr); 1821 ts->vec_dot = v; 1822 PetscFunctionReturn(0); 1823 } 1824 1825 /*@ 1826 TS2GetSolution - Returns the solution and time derivative at the present timestep 1827 for second order equations. It is valid to call this routine inside the function 1828 that you are evaluating in order to move to the new timestep. This vector not 1829 changed until the solution at the next timestep has been calculated. 1830 1831 Not Collective, but Vec returned is parallel if TS is parallel 1832 1833 Input Parameter: 1834 . ts - the TS context obtained from TSCreate() 1835 1836 Output Parameter: 1837 + u - the vector containing the solution 1838 - v - the vector containing the time derivative 1839 1840 Level: intermediate 1841 1842 .seealso: TS2SetSolution(), TSGetTimeStep(), TSGetTime() 1843 1844 .keywords: TS, timestep, get, solution 1845 @*/ 1846 PetscErrorCode TS2GetSolution(TS ts,Vec *u,Vec *v) 1847 { 1848 PetscFunctionBegin; 1849 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1850 if (u) PetscValidPointer(u,2); 1851 if (v) PetscValidPointer(v,3); 1852 if (u) *u = ts->vec_sol; 1853 if (v) *v = ts->vec_dot; 1854 PetscFunctionReturn(0); 1855 } 1856 1857 /*@C 1858 TSLoad - Loads a KSP that has been stored in binary with KSPView(). 1859 1860 Collective on PetscViewer 1861 1862 Input Parameters: 1863 + newdm - the newly loaded TS, this needs to have been created with TSCreate() or 1864 some related function before a call to TSLoad(). 1865 - viewer - binary file viewer, obtained from PetscViewerBinaryOpen() 1866 1867 Level: intermediate 1868 1869 Notes: 1870 The type is determined by the data in the file, any type set into the TS before this call is ignored. 1871 1872 Notes for advanced users: 1873 Most users should not need to know the details of the binary storage 1874 format, since TSLoad() and TSView() completely hide these details. 1875 But for anyone who's interested, the standard binary matrix storage 1876 format is 1877 .vb 1878 has not yet been determined 1879 .ve 1880 1881 .seealso: PetscViewerBinaryOpen(), TSView(), MatLoad(), VecLoad() 1882 @*/ 1883 PetscErrorCode TSLoad(TS ts, PetscViewer viewer) 1884 { 1885 PetscErrorCode ierr; 1886 PetscBool isbinary; 1887 PetscInt classid; 1888 char type[256]; 1889 DMTS sdm; 1890 DM dm; 1891 1892 PetscFunctionBegin; 1893 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1894 PetscValidHeaderSpecific(viewer,PETSC_VIEWER_CLASSID,2); 1895 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1896 if (!isbinary) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid viewer; open viewer with PetscViewerBinaryOpen()"); 1897 1898 ierr = PetscViewerBinaryRead(viewer,&classid,1,NULL,PETSC_INT);CHKERRQ(ierr); 1899 if (classid != TS_FILE_CLASSID) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONG,"Not TS next in file"); 1900 ierr = PetscViewerBinaryRead(viewer,type,256,NULL,PETSC_CHAR);CHKERRQ(ierr); 1901 ierr = TSSetType(ts, type);CHKERRQ(ierr); 1902 if (ts->ops->load) { 1903 ierr = (*ts->ops->load)(ts,viewer);CHKERRQ(ierr); 1904 } 1905 ierr = DMCreate(PetscObjectComm((PetscObject)ts),&dm);CHKERRQ(ierr); 1906 ierr = DMLoad(dm,viewer);CHKERRQ(ierr); 1907 ierr = TSSetDM(ts,dm);CHKERRQ(ierr); 1908 ierr = DMCreateGlobalVector(ts->dm,&ts->vec_sol);CHKERRQ(ierr); 1909 ierr = VecLoad(ts->vec_sol,viewer);CHKERRQ(ierr); 1910 ierr = DMGetDMTS(ts->dm,&sdm);CHKERRQ(ierr); 1911 ierr = DMTSLoad(sdm,viewer);CHKERRQ(ierr); 1912 PetscFunctionReturn(0); 1913 } 1914 1915 #include <petscdraw.h> 1916 #if defined(PETSC_HAVE_SAWS) 1917 #include <petscviewersaws.h> 1918 #endif 1919 /*@C 1920 TSView - Prints the TS data structure. 1921 1922 Collective on TS 1923 1924 Input Parameters: 1925 + ts - the TS context obtained from TSCreate() 1926 - viewer - visualization context 1927 1928 Options Database Key: 1929 . -ts_view - calls TSView() at end of TSStep() 1930 1931 Notes: 1932 The available visualization contexts include 1933 + PETSC_VIEWER_STDOUT_SELF - standard output (default) 1934 - PETSC_VIEWER_STDOUT_WORLD - synchronized standard 1935 output where only the first processor opens 1936 the file. All other processors send their 1937 data to the first processor to print. 1938 1939 The user can open an alternative visualization context with 1940 PetscViewerASCIIOpen() - output to a specified file. 1941 1942 Level: beginner 1943 1944 .keywords: TS, timestep, view 1945 1946 .seealso: PetscViewerASCIIOpen() 1947 @*/ 1948 PetscErrorCode TSView(TS ts,PetscViewer viewer) 1949 { 1950 PetscErrorCode ierr; 1951 TSType type; 1952 PetscBool iascii,isstring,isundials,isbinary,isdraw; 1953 DMTS sdm; 1954 #if defined(PETSC_HAVE_SAWS) 1955 PetscBool issaws; 1956 #endif 1957 1958 PetscFunctionBegin; 1959 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1960 if (!viewer) { 1961 ierr = PetscViewerASCIIGetStdout(PetscObjectComm((PetscObject)ts),&viewer);CHKERRQ(ierr); 1962 } 1963 PetscValidHeaderSpecific(viewer,PETSC_VIEWER_CLASSID,2); 1964 PetscCheckSameComm(ts,1,viewer,2); 1965 1966 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1967 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSTRING,&isstring);CHKERRQ(ierr); 1968 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1969 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1970 #if defined(PETSC_HAVE_SAWS) 1971 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSAWS,&issaws);CHKERRQ(ierr); 1972 #endif 1973 if (iascii) { 1974 ierr = PetscObjectPrintClassNamePrefixType((PetscObject)ts,viewer);CHKERRQ(ierr); 1975 if (ts->ops->view) { 1976 ierr = PetscViewerASCIIPushTab(viewer);CHKERRQ(ierr); 1977 ierr = (*ts->ops->view)(ts,viewer);CHKERRQ(ierr); 1978 ierr = PetscViewerASCIIPopTab(viewer);CHKERRQ(ierr); 1979 } 1980 if (ts->max_steps < PETSC_MAX_INT) { 1981 ierr = PetscViewerASCIIPrintf(viewer," maximum steps=%D\n",ts->max_steps);CHKERRQ(ierr); 1982 } 1983 if (ts->max_time < PETSC_MAX_REAL) { 1984 ierr = PetscViewerASCIIPrintf(viewer," maximum time=%g\n",(double)ts->max_time);CHKERRQ(ierr); 1985 } 1986 if (ts->usessnes) { 1987 PetscBool lin; 1988 if (ts->problem_type == TS_NONLINEAR) { 1989 ierr = PetscViewerASCIIPrintf(viewer," total number of nonlinear solver iterations=%D\n",ts->snes_its);CHKERRQ(ierr); 1990 } 1991 ierr = PetscViewerASCIIPrintf(viewer," total number of linear solver iterations=%D\n",ts->ksp_its);CHKERRQ(ierr); 1992 ierr = PetscObjectTypeCompare((PetscObject)ts->snes,SNESKSPONLY,&lin);CHKERRQ(ierr); 1993 ierr = PetscViewerASCIIPrintf(viewer," total number of %slinear solve failures=%D\n",lin ? "" : "non",ts->num_snes_failures);CHKERRQ(ierr); 1994 } 1995 ierr = PetscViewerASCIIPrintf(viewer," total number of rejected steps=%D\n",ts->reject);CHKERRQ(ierr); 1996 if (ts->vrtol) { 1997 ierr = PetscViewerASCIIPrintf(viewer," using vector of relative error tolerances, ");CHKERRQ(ierr); 1998 } else { 1999 ierr = PetscViewerASCIIPrintf(viewer," using relative error tolerance of %g, ",(double)ts->rtol);CHKERRQ(ierr); 2000 } 2001 if (ts->vatol) { 2002 ierr = PetscViewerASCIIPrintf(viewer," using vector of absolute error tolerances\n");CHKERRQ(ierr); 2003 } else { 2004 ierr = PetscViewerASCIIPrintf(viewer," using absolute error tolerance of %g\n",(double)ts->atol);CHKERRQ(ierr); 2005 } 2006 ierr = TSAdaptView(ts->adapt,viewer);CHKERRQ(ierr); 2007 if (ts->snes && ts->usessnes) {ierr = SNESView(ts->snes,viewer);CHKERRQ(ierr);} 2008 ierr = DMGetDMTS(ts->dm,&sdm);CHKERRQ(ierr); 2009 ierr = DMTSView(sdm,viewer);CHKERRQ(ierr); 2010 } else if (isstring) { 2011 ierr = TSGetType(ts,&type);CHKERRQ(ierr); 2012 ierr = PetscViewerStringSPrintf(viewer," %-7.7s",type);CHKERRQ(ierr); 2013 } else if (isbinary) { 2014 PetscInt classid = TS_FILE_CLASSID; 2015 MPI_Comm comm; 2016 PetscMPIInt rank; 2017 char type[256]; 2018 2019 ierr = PetscObjectGetComm((PetscObject)ts,&comm);CHKERRQ(ierr); 2020 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2021 if (!rank) { 2022 ierr = PetscViewerBinaryWrite(viewer,&classid,1,PETSC_INT,PETSC_FALSE);CHKERRQ(ierr); 2023 ierr = PetscStrncpy(type,((PetscObject)ts)->type_name,256);CHKERRQ(ierr); 2024 ierr = PetscViewerBinaryWrite(viewer,type,256,PETSC_CHAR,PETSC_FALSE);CHKERRQ(ierr); 2025 } 2026 if (ts->ops->view) { 2027 ierr = (*ts->ops->view)(ts,viewer);CHKERRQ(ierr); 2028 } 2029 if (ts->adapt) {ierr = TSAdaptView(ts->adapt,viewer);CHKERRQ(ierr);} 2030 ierr = DMView(ts->dm,viewer);CHKERRQ(ierr); 2031 ierr = VecView(ts->vec_sol,viewer);CHKERRQ(ierr); 2032 ierr = DMGetDMTS(ts->dm,&sdm);CHKERRQ(ierr); 2033 ierr = DMTSView(sdm,viewer);CHKERRQ(ierr); 2034 } else if (isdraw) { 2035 PetscDraw draw; 2036 char str[36]; 2037 PetscReal x,y,bottom,h; 2038 2039 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 2040 ierr = PetscDrawGetCurrentPoint(draw,&x,&y);CHKERRQ(ierr); 2041 ierr = PetscStrcpy(str,"TS: ");CHKERRQ(ierr); 2042 ierr = PetscStrcat(str,((PetscObject)ts)->type_name);CHKERRQ(ierr); 2043 ierr = PetscDrawStringBoxed(draw,x,y,PETSC_DRAW_BLACK,PETSC_DRAW_BLACK,str,NULL,&h);CHKERRQ(ierr); 2044 bottom = y - h; 2045 ierr = PetscDrawPushCurrentPoint(draw,x,bottom);CHKERRQ(ierr); 2046 if (ts->ops->view) { 2047 ierr = (*ts->ops->view)(ts,viewer);CHKERRQ(ierr); 2048 } 2049 if (ts->adapt) {ierr = TSAdaptView(ts->adapt,viewer);CHKERRQ(ierr);} 2050 if (ts->snes) {ierr = SNESView(ts->snes,viewer);CHKERRQ(ierr);} 2051 ierr = PetscDrawPopCurrentPoint(draw);CHKERRQ(ierr); 2052 #if defined(PETSC_HAVE_SAWS) 2053 } else if (issaws) { 2054 PetscMPIInt rank; 2055 const char *name; 2056 2057 ierr = PetscObjectGetName((PetscObject)ts,&name);CHKERRQ(ierr); 2058 ierr = MPI_Comm_rank(PETSC_COMM_WORLD,&rank);CHKERRQ(ierr); 2059 if (!((PetscObject)ts)->amsmem && !rank) { 2060 char dir[1024]; 2061 2062 ierr = PetscObjectViewSAWs((PetscObject)ts,viewer);CHKERRQ(ierr); 2063 ierr = PetscSNPrintf(dir,1024,"/PETSc/Objects/%s/time_step",name);CHKERRQ(ierr); 2064 PetscStackCallSAWs(SAWs_Register,(dir,&ts->steps,1,SAWs_READ,SAWs_INT)); 2065 ierr = PetscSNPrintf(dir,1024,"/PETSc/Objects/%s/time",name);CHKERRQ(ierr); 2066 PetscStackCallSAWs(SAWs_Register,(dir,&ts->ptime,1,SAWs_READ,SAWs_DOUBLE)); 2067 } 2068 if (ts->ops->view) { 2069 ierr = (*ts->ops->view)(ts,viewer);CHKERRQ(ierr); 2070 } 2071 #endif 2072 } 2073 2074 ierr = PetscViewerASCIIPushTab(viewer);CHKERRQ(ierr); 2075 ierr = PetscObjectTypeCompare((PetscObject)ts,TSSUNDIALS,&isundials);CHKERRQ(ierr); 2076 ierr = PetscViewerASCIIPopTab(viewer);CHKERRQ(ierr); 2077 PetscFunctionReturn(0); 2078 } 2079 2080 /*@ 2081 TSSetApplicationContext - Sets an optional user-defined context for 2082 the timesteppers. 2083 2084 Logically Collective on TS 2085 2086 Input Parameters: 2087 + ts - the TS context obtained from TSCreate() 2088 - usrP - optional user context 2089 2090 Fortran Notes: To use this from Fortran you must write a Fortran interface definition for this 2091 function that tells Fortran the Fortran derived data type that you are passing in as the ctx argument. 2092 2093 Level: intermediate 2094 2095 .keywords: TS, timestep, set, application, context 2096 2097 .seealso: TSGetApplicationContext() 2098 @*/ 2099 PetscErrorCode TSSetApplicationContext(TS ts,void *usrP) 2100 { 2101 PetscFunctionBegin; 2102 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2103 ts->user = usrP; 2104 PetscFunctionReturn(0); 2105 } 2106 2107 /*@ 2108 TSGetApplicationContext - Gets the user-defined context for the 2109 timestepper. 2110 2111 Not Collective 2112 2113 Input Parameter: 2114 . ts - the TS context obtained from TSCreate() 2115 2116 Output Parameter: 2117 . usrP - user context 2118 2119 Fortran Notes: To use this from Fortran you must write a Fortran interface definition for this 2120 function that tells Fortran the Fortran derived data type that you are passing in as the ctx argument. 2121 2122 Level: intermediate 2123 2124 .keywords: TS, timestep, get, application, context 2125 2126 .seealso: TSSetApplicationContext() 2127 @*/ 2128 PetscErrorCode TSGetApplicationContext(TS ts,void *usrP) 2129 { 2130 PetscFunctionBegin; 2131 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2132 *(void**)usrP = ts->user; 2133 PetscFunctionReturn(0); 2134 } 2135 2136 /*@ 2137 TSGetStepNumber - Gets the number of steps completed. 2138 2139 Not Collective 2140 2141 Input Parameter: 2142 . ts - the TS context obtained from TSCreate() 2143 2144 Output Parameter: 2145 . steps - number of steps completed so far 2146 2147 Level: intermediate 2148 2149 .keywords: TS, timestep, get, iteration, number 2150 .seealso: TSGetTime(), TSGetTimeStep(), TSSetPreStep(), TSSetPreStage(), TSSetPostStage(), TSSetPostStep() 2151 @*/ 2152 PetscErrorCode TSGetStepNumber(TS ts,PetscInt *steps) 2153 { 2154 PetscFunctionBegin; 2155 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2156 PetscValidIntPointer(steps,2); 2157 *steps = ts->steps; 2158 PetscFunctionReturn(0); 2159 } 2160 2161 /*@ 2162 TSSetStepNumber - Sets the number of steps completed. 2163 2164 Logically Collective on TS 2165 2166 Input Parameters: 2167 + ts - the TS context 2168 - steps - number of steps completed so far 2169 2170 Notes: 2171 For most uses of the TS solvers the user need not explicitly call 2172 TSSetStepNumber(), as the step counter is appropriately updated in 2173 TSSolve()/TSStep()/TSRollBack(). Power users may call this routine to 2174 reinitialize timestepping by setting the step counter to zero (and time 2175 to the initial time) to solve a similar problem with different initial 2176 conditions or parameters. Other possible use case is to continue 2177 timestepping from a previously interrupted run in such a way that TS 2178 monitors will be called with a initial nonzero step counter. 2179 2180 Level: advanced 2181 2182 .keywords: TS, timestep, set, iteration, number 2183 .seealso: TSGetStepNumber(), TSSetTime(), TSSetTimeStep(), TSSetSolution() 2184 @*/ 2185 PetscErrorCode TSSetStepNumber(TS ts,PetscInt steps) 2186 { 2187 PetscFunctionBegin; 2188 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2189 PetscValidLogicalCollectiveInt(ts,steps,2); 2190 if (steps < 0) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_OUTOFRANGE,"Step number must be non-negative"); 2191 ts->steps = steps; 2192 PetscFunctionReturn(0); 2193 } 2194 2195 /*@ 2196 TSSetTimeStep - Allows one to reset the timestep at any time, 2197 useful for simple pseudo-timestepping codes. 2198 2199 Logically Collective on TS 2200 2201 Input Parameters: 2202 + ts - the TS context obtained from TSCreate() 2203 - time_step - the size of the timestep 2204 2205 Level: intermediate 2206 2207 .seealso: TSGetTimeStep(), TSSetTime() 2208 2209 .keywords: TS, set, timestep 2210 @*/ 2211 PetscErrorCode TSSetTimeStep(TS ts,PetscReal time_step) 2212 { 2213 PetscFunctionBegin; 2214 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2215 PetscValidLogicalCollectiveReal(ts,time_step,2); 2216 ts->time_step = time_step; 2217 PetscFunctionReturn(0); 2218 } 2219 2220 /*@ 2221 TSSetExactFinalTime - Determines whether to adapt the final time step to 2222 match the exact final time, interpolate solution to the exact final time, 2223 or just return at the final time TS computed. 2224 2225 Logically Collective on TS 2226 2227 Input Parameter: 2228 + ts - the time-step context 2229 - eftopt - exact final time option 2230 2231 $ TS_EXACTFINALTIME_STEPOVER - Don't do anything if final time is exceeded 2232 $ TS_EXACTFINALTIME_INTERPOLATE - Interpolate back to final time 2233 $ TS_EXACTFINALTIME_MATCHSTEP - Adapt final time step to match the final time 2234 2235 Options Database: 2236 . -ts_exact_final_time <stepover,interpolate,matchstep> - select the final step at runtime 2237 2238 Warning: If you use the option TS_EXACTFINALTIME_STEPOVER the solution may be at a very different time 2239 then the final time you selected. 2240 2241 Level: beginner 2242 2243 .seealso: TSExactFinalTimeOption, TSGetExactFinalTime() 2244 @*/ 2245 PetscErrorCode TSSetExactFinalTime(TS ts,TSExactFinalTimeOption eftopt) 2246 { 2247 PetscFunctionBegin; 2248 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2249 PetscValidLogicalCollectiveEnum(ts,eftopt,2); 2250 ts->exact_final_time = eftopt; 2251 PetscFunctionReturn(0); 2252 } 2253 2254 /*@ 2255 TSGetExactFinalTime - Gets the exact final time option. 2256 2257 Not Collective 2258 2259 Input Parameter: 2260 . ts - the TS context 2261 2262 Output Parameter: 2263 . eftopt - exact final time option 2264 2265 Level: beginner 2266 2267 .seealso: TSExactFinalTimeOption, TSSetExactFinalTime() 2268 @*/ 2269 PetscErrorCode TSGetExactFinalTime(TS ts,TSExactFinalTimeOption *eftopt) 2270 { 2271 PetscFunctionBegin; 2272 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2273 PetscValidPointer(eftopt,2); 2274 *eftopt = ts->exact_final_time; 2275 PetscFunctionReturn(0); 2276 } 2277 2278 /*@ 2279 TSGetTimeStep - Gets the current timestep size. 2280 2281 Not Collective 2282 2283 Input Parameter: 2284 . ts - the TS context obtained from TSCreate() 2285 2286 Output Parameter: 2287 . dt - the current timestep size 2288 2289 Level: intermediate 2290 2291 .seealso: TSSetTimeStep(), TSGetTime() 2292 2293 .keywords: TS, get, timestep 2294 @*/ 2295 PetscErrorCode TSGetTimeStep(TS ts,PetscReal *dt) 2296 { 2297 PetscFunctionBegin; 2298 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2299 PetscValidRealPointer(dt,2); 2300 *dt = ts->time_step; 2301 PetscFunctionReturn(0); 2302 } 2303 2304 /*@ 2305 TSGetSolution - Returns the solution at the present timestep. It 2306 is valid to call this routine inside the function that you are evaluating 2307 in order to move to the new timestep. This vector not changed until 2308 the solution at the next timestep has been calculated. 2309 2310 Not Collective, but Vec returned is parallel if TS is parallel 2311 2312 Input Parameter: 2313 . ts - the TS context obtained from TSCreate() 2314 2315 Output Parameter: 2316 . v - the vector containing the solution 2317 2318 Note: If you used TSSetExactFinalTime(ts,TS_EXACTFINALTIME_MATCHSTEP); this does not return the solution at the requested 2319 final time. It returns the solution at the next timestep. 2320 2321 Level: intermediate 2322 2323 .seealso: TSGetTimeStep(), TSGetTime(), TSGetSolveTime(), TSGetSolutionComponents() 2324 2325 .keywords: TS, timestep, get, solution 2326 @*/ 2327 PetscErrorCode TSGetSolution(TS ts,Vec *v) 2328 { 2329 PetscFunctionBegin; 2330 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2331 PetscValidPointer(v,2); 2332 *v = ts->vec_sol; 2333 PetscFunctionReturn(0); 2334 } 2335 2336 /*@ 2337 TSGetSolutionComponents - Returns any solution components at the present 2338 timestep, if available for the time integration method being used. 2339 Solution components are quantities that share the same size and 2340 structure as the solution vector. 2341 2342 Not Collective, but Vec returned is parallel if TS is parallel 2343 2344 Parameters : 2345 . ts - the TS context obtained from TSCreate() (input parameter). 2346 . n - If v is PETSC_NULL, then the number of solution components is 2347 returned through n, else the n-th solution component is 2348 returned in v. 2349 . v - the vector containing the n-th solution component 2350 (may be PETSC_NULL to use this function to find out 2351 the number of solutions components). 2352 2353 Level: advanced 2354 2355 .seealso: TSGetSolution() 2356 2357 .keywords: TS, timestep, get, solution 2358 @*/ 2359 PetscErrorCode TSGetSolutionComponents(TS ts,PetscInt *n,Vec *v) 2360 { 2361 PetscErrorCode ierr; 2362 2363 PetscFunctionBegin; 2364 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2365 if (!ts->ops->getsolutioncomponents) *n = 0; 2366 else { 2367 ierr = (*ts->ops->getsolutioncomponents)(ts,n,v);CHKERRQ(ierr); 2368 } 2369 PetscFunctionReturn(0); 2370 } 2371 2372 /*@ 2373 TSGetAuxSolution - Returns an auxiliary solution at the present 2374 timestep, if available for the time integration method being used. 2375 2376 Not Collective, but Vec returned is parallel if TS is parallel 2377 2378 Parameters : 2379 . ts - the TS context obtained from TSCreate() (input parameter). 2380 . v - the vector containing the auxiliary solution 2381 2382 Level: intermediate 2383 2384 .seealso: TSGetSolution() 2385 2386 .keywords: TS, timestep, get, solution 2387 @*/ 2388 PetscErrorCode TSGetAuxSolution(TS ts,Vec *v) 2389 { 2390 PetscErrorCode ierr; 2391 2392 PetscFunctionBegin; 2393 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2394 if (ts->ops->getauxsolution) { 2395 ierr = (*ts->ops->getauxsolution)(ts,v);CHKERRQ(ierr); 2396 } else { 2397 ierr = VecZeroEntries(*v); CHKERRQ(ierr); 2398 } 2399 PetscFunctionReturn(0); 2400 } 2401 2402 /*@ 2403 TSGetTimeError - Returns the estimated error vector, if the chosen 2404 TSType has an error estimation functionality. 2405 2406 Not Collective, but Vec returned is parallel if TS is parallel 2407 2408 Note: MUST call after TSSetUp() 2409 2410 Parameters : 2411 . ts - the TS context obtained from TSCreate() (input parameter). 2412 . n - current estimate (n=0) or previous one (n=-1) 2413 . v - the vector containing the error (same size as the solution). 2414 2415 Level: intermediate 2416 2417 .seealso: TSGetSolution(), TSSetTimeError() 2418 2419 .keywords: TS, timestep, get, error 2420 @*/ 2421 PetscErrorCode TSGetTimeError(TS ts,PetscInt n,Vec *v) 2422 { 2423 PetscErrorCode ierr; 2424 2425 PetscFunctionBegin; 2426 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2427 if (ts->ops->gettimeerror) { 2428 ierr = (*ts->ops->gettimeerror)(ts,n,v);CHKERRQ(ierr); 2429 } else { 2430 ierr = VecZeroEntries(*v);CHKERRQ(ierr); 2431 } 2432 PetscFunctionReturn(0); 2433 } 2434 2435 /*@ 2436 TSSetTimeError - Sets the estimated error vector, if the chosen 2437 TSType has an error estimation functionality. This can be used 2438 to restart such a time integrator with a given error vector. 2439 2440 Not Collective, but Vec returned is parallel if TS is parallel 2441 2442 Parameters : 2443 . ts - the TS context obtained from TSCreate() (input parameter). 2444 . v - the vector containing the error (same size as the solution). 2445 2446 Level: intermediate 2447 2448 .seealso: TSSetSolution(), TSGetTimeError) 2449 2450 .keywords: TS, timestep, get, error 2451 @*/ 2452 PetscErrorCode TSSetTimeError(TS ts,Vec v) 2453 { 2454 PetscErrorCode ierr; 2455 2456 PetscFunctionBegin; 2457 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2458 if (!ts->setupcalled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Must call TSSetUp() first"); 2459 if (ts->ops->settimeerror) { 2460 ierr = (*ts->ops->settimeerror)(ts,v);CHKERRQ(ierr); 2461 } 2462 PetscFunctionReturn(0); 2463 } 2464 2465 /*@ 2466 TSGetCostGradients - Returns the gradients from the TSAdjointSolve() 2467 2468 Not Collective, but Vec returned is parallel if TS is parallel 2469 2470 Input Parameter: 2471 . ts - the TS context obtained from TSCreate() 2472 2473 Output Parameter: 2474 + lambda - vectors containing the gradients of the cost functions with respect to the ODE/DAE solution variables 2475 - mu - vectors containing the gradients of the cost functions with respect to the problem parameters 2476 2477 Level: intermediate 2478 2479 .seealso: TSGetTimeStep() 2480 2481 .keywords: TS, timestep, get, sensitivity 2482 @*/ 2483 PetscErrorCode TSGetCostGradients(TS ts,PetscInt *numcost,Vec **lambda,Vec **mu) 2484 { 2485 PetscFunctionBegin; 2486 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2487 if (numcost) *numcost = ts->numcost; 2488 if (lambda) *lambda = ts->vecs_sensi; 2489 if (mu) *mu = ts->vecs_sensip; 2490 PetscFunctionReturn(0); 2491 } 2492 2493 /* ----- Routines to initialize and destroy a timestepper ---- */ 2494 /*@ 2495 TSSetProblemType - Sets the type of problem to be solved. 2496 2497 Not collective 2498 2499 Input Parameters: 2500 + ts - The TS 2501 - type - One of TS_LINEAR, TS_NONLINEAR where these types refer to problems of the forms 2502 .vb 2503 U_t - A U = 0 (linear) 2504 U_t - A(t) U = 0 (linear) 2505 F(t,U,U_t) = 0 (nonlinear) 2506 .ve 2507 2508 Level: beginner 2509 2510 .keywords: TS, problem type 2511 .seealso: TSSetUp(), TSProblemType, TS 2512 @*/ 2513 PetscErrorCode TSSetProblemType(TS ts, TSProblemType type) 2514 { 2515 PetscErrorCode ierr; 2516 2517 PetscFunctionBegin; 2518 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 2519 ts->problem_type = type; 2520 if (type == TS_LINEAR) { 2521 SNES snes; 2522 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 2523 ierr = SNESSetType(snes,SNESKSPONLY);CHKERRQ(ierr); 2524 } 2525 PetscFunctionReturn(0); 2526 } 2527 2528 /*@C 2529 TSGetProblemType - Gets the type of problem to be solved. 2530 2531 Not collective 2532 2533 Input Parameter: 2534 . ts - The TS 2535 2536 Output Parameter: 2537 . type - One of TS_LINEAR, TS_NONLINEAR where these types refer to problems of the forms 2538 .vb 2539 M U_t = A U 2540 M(t) U_t = A(t) U 2541 F(t,U,U_t) 2542 .ve 2543 2544 Level: beginner 2545 2546 .keywords: TS, problem type 2547 .seealso: TSSetUp(), TSProblemType, TS 2548 @*/ 2549 PetscErrorCode TSGetProblemType(TS ts, TSProblemType *type) 2550 { 2551 PetscFunctionBegin; 2552 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 2553 PetscValidIntPointer(type,2); 2554 *type = ts->problem_type; 2555 PetscFunctionReturn(0); 2556 } 2557 2558 /*@ 2559 TSSetUp - Sets up the internal data structures for the later use 2560 of a timestepper. 2561 2562 Collective on TS 2563 2564 Input Parameter: 2565 . ts - the TS context obtained from TSCreate() 2566 2567 Notes: 2568 For basic use of the TS solvers the user need not explicitly call 2569 TSSetUp(), since these actions will automatically occur during 2570 the call to TSStep() or TSSolve(). However, if one wishes to control this 2571 phase separately, TSSetUp() should be called after TSCreate() 2572 and optional routines of the form TSSetXXX(), but before TSStep() and TSSolve(). 2573 2574 Level: advanced 2575 2576 .keywords: TS, timestep, setup 2577 2578 .seealso: TSCreate(), TSStep(), TSDestroy(), TSSolve() 2579 @*/ 2580 PetscErrorCode TSSetUp(TS ts) 2581 { 2582 PetscErrorCode ierr; 2583 DM dm; 2584 PetscErrorCode (*func)(SNES,Vec,Vec,void*); 2585 PetscErrorCode (*jac)(SNES,Vec,Mat,Mat,void*); 2586 TSIFunction ifun; 2587 TSIJacobian ijac; 2588 TSI2Jacobian i2jac; 2589 TSRHSJacobian rhsjac; 2590 PetscBool isnone; 2591 2592 PetscFunctionBegin; 2593 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2594 if (ts->setupcalled) PetscFunctionReturn(0); 2595 2596 if (!((PetscObject)ts)->type_name) { 2597 ierr = TSGetIFunction(ts,NULL,&ifun,NULL);CHKERRQ(ierr); 2598 ierr = TSSetType(ts,ifun ? TSBEULER : TSEULER);CHKERRQ(ierr); 2599 } 2600 2601 if (!ts->vec_sol) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Must call TSSetSolution() first"); 2602 2603 if (ts->rhsjacobian.reuse) { 2604 Mat Amat,Pmat; 2605 SNES snes; 2606 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 2607 ierr = SNESGetJacobian(snes,&Amat,&Pmat,NULL,NULL);CHKERRQ(ierr); 2608 /* Matching matrices implies that an IJacobian is NOT set, because if it had been set, the IJacobian's matrix would 2609 * have displaced the RHS matrix */ 2610 if (Amat == ts->Arhs) { 2611 /* we need to copy the values of the matrix because for the constant Jacobian case the user will never set the numerical values in this new location */ 2612 ierr = MatDuplicate(ts->Arhs,MAT_COPY_VALUES,&Amat);CHKERRQ(ierr); 2613 ierr = SNESSetJacobian(snes,Amat,NULL,NULL,NULL);CHKERRQ(ierr); 2614 ierr = MatDestroy(&Amat);CHKERRQ(ierr); 2615 } 2616 if (Pmat == ts->Brhs) { 2617 ierr = MatDuplicate(ts->Brhs,MAT_COPY_VALUES,&Pmat);CHKERRQ(ierr); 2618 ierr = SNESSetJacobian(snes,NULL,Pmat,NULL,NULL);CHKERRQ(ierr); 2619 ierr = MatDestroy(&Pmat);CHKERRQ(ierr); 2620 } 2621 } 2622 2623 ierr = TSGetAdapt(ts,&ts->adapt);CHKERRQ(ierr); 2624 ierr = TSAdaptSetDefaultType(ts->adapt,ts->default_adapt_type);CHKERRQ(ierr); 2625 2626 if (ts->ops->setup) { 2627 ierr = (*ts->ops->setup)(ts);CHKERRQ(ierr); 2628 } 2629 2630 /* Attempt to check/preset a default value for the exact final time option */ 2631 ierr = PetscObjectTypeCompare((PetscObject)ts->adapt,TSADAPTNONE,&isnone);CHKERRQ(ierr); 2632 if (!isnone && ts->exact_final_time == TS_EXACTFINALTIME_UNSPECIFIED) 2633 ts->exact_final_time = TS_EXACTFINALTIME_MATCHSTEP; 2634 2635 /* In the case where we've set a DMTSFunction or what have you, we need the default SNESFunction 2636 to be set right but can't do it elsewhere due to the overreliance on ctx=ts. 2637 */ 2638 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 2639 ierr = DMSNESGetFunction(dm,&func,NULL);CHKERRQ(ierr); 2640 if (!func) { 2641 ierr = DMSNESSetFunction(dm,SNESTSFormFunction,ts);CHKERRQ(ierr); 2642 } 2643 /* If the SNES doesn't have a jacobian set and the TS has an ijacobian or rhsjacobian set, set the SNES to use it. 2644 Otherwise, the SNES will use coloring internally to form the Jacobian. 2645 */ 2646 ierr = DMSNESGetJacobian(dm,&jac,NULL);CHKERRQ(ierr); 2647 ierr = DMTSGetIJacobian(dm,&ijac,NULL);CHKERRQ(ierr); 2648 ierr = DMTSGetI2Jacobian(dm,&i2jac,NULL);CHKERRQ(ierr); 2649 ierr = DMTSGetRHSJacobian(dm,&rhsjac,NULL);CHKERRQ(ierr); 2650 if (!jac && (ijac || i2jac || rhsjac)) { 2651 ierr = DMSNESSetJacobian(dm,SNESTSFormJacobian,ts);CHKERRQ(ierr); 2652 } 2653 2654 /* if time integration scheme has a starting method, call it */ 2655 if (ts->ops->startingmethod) { 2656 ierr = (*ts->ops->startingmethod)(ts);CHKERRQ(ierr); 2657 } 2658 2659 ts->setupcalled = PETSC_TRUE; 2660 PetscFunctionReturn(0); 2661 } 2662 2663 /*@ 2664 TSAdjointSetUp - Sets up the internal data structures for the later use 2665 of an adjoint solver 2666 2667 Collective on TS 2668 2669 Input Parameter: 2670 . ts - the TS context obtained from TSCreate() 2671 2672 Level: advanced 2673 2674 .keywords: TS, timestep, setup 2675 2676 .seealso: TSCreate(), TSAdjointStep(), TSSetCostGradients() 2677 @*/ 2678 PetscErrorCode TSAdjointSetUp(TS ts) 2679 { 2680 PetscErrorCode ierr; 2681 2682 PetscFunctionBegin; 2683 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2684 if (ts->adjointsetupcalled) PetscFunctionReturn(0); 2685 if (!ts->vecs_sensi) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONGSTATE,"Must call TSSetCostGradients() first"); 2686 if (ts->vecs_sensip && !ts->Jacp) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONGSTATE,"Must call TSAdjointSetRHSJacobian() first"); 2687 2688 if (ts->vec_costintegral) { /* if there is integral in the cost function */ 2689 ierr = VecDuplicateVecs(ts->vecs_sensi[0],ts->numcost,&ts->vecs_drdy);CHKERRQ(ierr); 2690 if (ts->vecs_sensip){ 2691 ierr = VecDuplicateVecs(ts->vecs_sensip[0],ts->numcost,&ts->vecs_drdp);CHKERRQ(ierr); 2692 } 2693 } 2694 2695 if (ts->ops->adjointsetup) { 2696 ierr = (*ts->ops->adjointsetup)(ts);CHKERRQ(ierr); 2697 } 2698 ts->adjointsetupcalled = PETSC_TRUE; 2699 PetscFunctionReturn(0); 2700 } 2701 2702 /*@ 2703 TSReset - Resets a TS context and removes any allocated Vecs and Mats. 2704 2705 Collective on TS 2706 2707 Input Parameter: 2708 . ts - the TS context obtained from TSCreate() 2709 2710 Level: beginner 2711 2712 .keywords: TS, timestep, reset 2713 2714 .seealso: TSCreate(), TSSetup(), TSDestroy() 2715 @*/ 2716 PetscErrorCode TSReset(TS ts) 2717 { 2718 PetscErrorCode ierr; 2719 2720 PetscFunctionBegin; 2721 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2722 2723 if (ts->ops->reset) { 2724 ierr = (*ts->ops->reset)(ts);CHKERRQ(ierr); 2725 } 2726 if (ts->snes) {ierr = SNESReset(ts->snes);CHKERRQ(ierr);} 2727 if (ts->adapt) {ierr = TSAdaptReset(ts->adapt);CHKERRQ(ierr);} 2728 2729 ierr = MatDestroy(&ts->Arhs);CHKERRQ(ierr); 2730 ierr = MatDestroy(&ts->Brhs);CHKERRQ(ierr); 2731 ierr = VecDestroy(&ts->Frhs);CHKERRQ(ierr); 2732 ierr = VecDestroy(&ts->vec_sol);CHKERRQ(ierr); 2733 ierr = VecDestroy(&ts->vec_dot);CHKERRQ(ierr); 2734 ierr = VecDestroy(&ts->vatol);CHKERRQ(ierr); 2735 ierr = VecDestroy(&ts->vrtol);CHKERRQ(ierr); 2736 ierr = VecDestroyVecs(ts->nwork,&ts->work);CHKERRQ(ierr); 2737 2738 ierr = VecDestroyVecs(ts->numcost,&ts->vecs_drdy);CHKERRQ(ierr); 2739 ierr = VecDestroyVecs(ts->numcost,&ts->vecs_drdp);CHKERRQ(ierr); 2740 2741 ierr = MatDestroy(&ts->Jacp);CHKERRQ(ierr); 2742 ierr = VecDestroy(&ts->vec_costintegral);CHKERRQ(ierr); 2743 ierr = VecDestroy(&ts->vec_costintegrand);CHKERRQ(ierr); 2744 2745 ierr = PetscFree(ts->vecs_fwdsensipacked);CHKERRQ(ierr); 2746 2747 ts->setupcalled = PETSC_FALSE; 2748 PetscFunctionReturn(0); 2749 } 2750 2751 /*@ 2752 TSDestroy - Destroys the timestepper context that was created 2753 with TSCreate(). 2754 2755 Collective on TS 2756 2757 Input Parameter: 2758 . ts - the TS context obtained from TSCreate() 2759 2760 Level: beginner 2761 2762 .keywords: TS, timestepper, destroy 2763 2764 .seealso: TSCreate(), TSSetUp(), TSSolve() 2765 @*/ 2766 PetscErrorCode TSDestroy(TS *ts) 2767 { 2768 PetscErrorCode ierr; 2769 2770 PetscFunctionBegin; 2771 if (!*ts) PetscFunctionReturn(0); 2772 PetscValidHeaderSpecific((*ts),TS_CLASSID,1); 2773 if (--((PetscObject)(*ts))->refct > 0) {*ts = 0; PetscFunctionReturn(0);} 2774 2775 ierr = TSReset((*ts));CHKERRQ(ierr); 2776 2777 /* if memory was published with SAWs then destroy it */ 2778 ierr = PetscObjectSAWsViewOff((PetscObject)*ts);CHKERRQ(ierr); 2779 if ((*ts)->ops->destroy) {ierr = (*(*ts)->ops->destroy)((*ts));CHKERRQ(ierr);} 2780 2781 ierr = TSTrajectoryDestroy(&(*ts)->trajectory);CHKERRQ(ierr); 2782 2783 ierr = TSAdaptDestroy(&(*ts)->adapt);CHKERRQ(ierr); 2784 ierr = TSEventDestroy(&(*ts)->event);CHKERRQ(ierr); 2785 2786 ierr = SNESDestroy(&(*ts)->snes);CHKERRQ(ierr); 2787 ierr = DMDestroy(&(*ts)->dm);CHKERRQ(ierr); 2788 ierr = TSMonitorCancel((*ts));CHKERRQ(ierr); 2789 ierr = TSAdjointMonitorCancel((*ts));CHKERRQ(ierr); 2790 2791 ierr = PetscHeaderDestroy(ts);CHKERRQ(ierr); 2792 PetscFunctionReturn(0); 2793 } 2794 2795 /*@ 2796 TSGetSNES - Returns the SNES (nonlinear solver) associated with 2797 a TS (timestepper) context. Valid only for nonlinear problems. 2798 2799 Not Collective, but SNES is parallel if TS is parallel 2800 2801 Input Parameter: 2802 . ts - the TS context obtained from TSCreate() 2803 2804 Output Parameter: 2805 . snes - the nonlinear solver context 2806 2807 Notes: 2808 The user can then directly manipulate the SNES context to set various 2809 options, etc. Likewise, the user can then extract and manipulate the 2810 KSP, KSP, and PC contexts as well. 2811 2812 TSGetSNES() does not work for integrators that do not use SNES; in 2813 this case TSGetSNES() returns NULL in snes. 2814 2815 Level: beginner 2816 2817 .keywords: timestep, get, SNES 2818 @*/ 2819 PetscErrorCode TSGetSNES(TS ts,SNES *snes) 2820 { 2821 PetscErrorCode ierr; 2822 2823 PetscFunctionBegin; 2824 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2825 PetscValidPointer(snes,2); 2826 if (!ts->snes) { 2827 ierr = SNESCreate(PetscObjectComm((PetscObject)ts),&ts->snes);CHKERRQ(ierr); 2828 ierr = SNESSetFunction(ts->snes,NULL,SNESTSFormFunction,ts);CHKERRQ(ierr); 2829 ierr = PetscLogObjectParent((PetscObject)ts,(PetscObject)ts->snes);CHKERRQ(ierr); 2830 ierr = PetscObjectIncrementTabLevel((PetscObject)ts->snes,(PetscObject)ts,1);CHKERRQ(ierr); 2831 if (ts->dm) {ierr = SNESSetDM(ts->snes,ts->dm);CHKERRQ(ierr);} 2832 if (ts->problem_type == TS_LINEAR) { 2833 ierr = SNESSetType(ts->snes,SNESKSPONLY);CHKERRQ(ierr); 2834 } 2835 } 2836 *snes = ts->snes; 2837 PetscFunctionReturn(0); 2838 } 2839 2840 /*@ 2841 TSSetSNES - Set the SNES (nonlinear solver) to be used by the timestepping context 2842 2843 Collective 2844 2845 Input Parameter: 2846 + ts - the TS context obtained from TSCreate() 2847 - snes - the nonlinear solver context 2848 2849 Notes: 2850 Most users should have the TS created by calling TSGetSNES() 2851 2852 Level: developer 2853 2854 .keywords: timestep, set, SNES 2855 @*/ 2856 PetscErrorCode TSSetSNES(TS ts,SNES snes) 2857 { 2858 PetscErrorCode ierr; 2859 PetscErrorCode (*func)(SNES,Vec,Mat,Mat,void*); 2860 2861 PetscFunctionBegin; 2862 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2863 PetscValidHeaderSpecific(snes,SNES_CLASSID,2); 2864 ierr = PetscObjectReference((PetscObject)snes);CHKERRQ(ierr); 2865 ierr = SNESDestroy(&ts->snes);CHKERRQ(ierr); 2866 2867 ts->snes = snes; 2868 2869 ierr = SNESSetFunction(ts->snes,NULL,SNESTSFormFunction,ts);CHKERRQ(ierr); 2870 ierr = SNESGetJacobian(ts->snes,NULL,NULL,&func,NULL);CHKERRQ(ierr); 2871 if (func == SNESTSFormJacobian) { 2872 ierr = SNESSetJacobian(ts->snes,NULL,NULL,SNESTSFormJacobian,ts);CHKERRQ(ierr); 2873 } 2874 PetscFunctionReturn(0); 2875 } 2876 2877 /*@ 2878 TSGetKSP - Returns the KSP (linear solver) associated with 2879 a TS (timestepper) context. 2880 2881 Not Collective, but KSP is parallel if TS is parallel 2882 2883 Input Parameter: 2884 . ts - the TS context obtained from TSCreate() 2885 2886 Output Parameter: 2887 . ksp - the nonlinear solver context 2888 2889 Notes: 2890 The user can then directly manipulate the KSP context to set various 2891 options, etc. Likewise, the user can then extract and manipulate the 2892 KSP and PC contexts as well. 2893 2894 TSGetKSP() does not work for integrators that do not use KSP; 2895 in this case TSGetKSP() returns NULL in ksp. 2896 2897 Level: beginner 2898 2899 .keywords: timestep, get, KSP 2900 @*/ 2901 PetscErrorCode TSGetKSP(TS ts,KSP *ksp) 2902 { 2903 PetscErrorCode ierr; 2904 SNES snes; 2905 2906 PetscFunctionBegin; 2907 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2908 PetscValidPointer(ksp,2); 2909 if (!((PetscObject)ts)->type_name) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_NULL,"KSP is not created yet. Call TSSetType() first"); 2910 if (ts->problem_type != TS_LINEAR) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Linear only; use TSGetSNES()"); 2911 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 2912 ierr = SNESGetKSP(snes,ksp);CHKERRQ(ierr); 2913 PetscFunctionReturn(0); 2914 } 2915 2916 /* ----------- Routines to set solver parameters ---------- */ 2917 2918 /*@ 2919 TSSetMaxSteps - Sets the maximum number of steps to use. 2920 2921 Logically Collective on TS 2922 2923 Input Parameters: 2924 + ts - the TS context obtained from TSCreate() 2925 - maxsteps - maximum number of steps to use 2926 2927 Options Database Keys: 2928 . -ts_max_steps <maxsteps> - Sets maxsteps 2929 2930 Notes: 2931 The default maximum number of steps is 5000 2932 2933 Level: intermediate 2934 2935 .keywords: TS, timestep, set, maximum, steps 2936 2937 .seealso: TSGetMaxSteps(), TSSetMaxTime(), TSSetExactFinalTime() 2938 @*/ 2939 PetscErrorCode TSSetMaxSteps(TS ts,PetscInt maxsteps) 2940 { 2941 PetscFunctionBegin; 2942 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2943 PetscValidLogicalCollectiveInt(ts,maxsteps,2); 2944 if (maxsteps < 0 ) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_OUTOFRANGE,"Maximum number of steps must be non-negative"); 2945 ts->max_steps = maxsteps; 2946 PetscFunctionReturn(0); 2947 } 2948 2949 /*@ 2950 TSGetMaxSteps - Gets the maximum number of steps to use. 2951 2952 Not Collective 2953 2954 Input Parameters: 2955 . ts - the TS context obtained from TSCreate() 2956 2957 Output Parameter: 2958 . maxsteps - maximum number of steps to use 2959 2960 Level: advanced 2961 2962 .keywords: TS, timestep, get, maximum, steps 2963 2964 .seealso: TSSetMaxSteps(), TSGetMaxTime(), TSSetMaxTime() 2965 @*/ 2966 PetscErrorCode TSGetMaxSteps(TS ts,PetscInt *maxsteps) 2967 { 2968 PetscFunctionBegin; 2969 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2970 PetscValidIntPointer(maxsteps,2); 2971 *maxsteps = ts->max_steps; 2972 PetscFunctionReturn(0); 2973 } 2974 2975 /*@ 2976 TSSetMaxTime - Sets the maximum (or final) time for timestepping. 2977 2978 Logically Collective on TS 2979 2980 Input Parameters: 2981 + ts - the TS context obtained from TSCreate() 2982 - maxtime - final time to step to 2983 2984 Options Database Keys: 2985 . -ts_max_time <maxtime> - Sets maxtime 2986 2987 Notes: 2988 The default maximum time is 5.0 2989 2990 Level: intermediate 2991 2992 .keywords: TS, timestep, set, maximum, time 2993 2994 .seealso: TSGetMaxTime(), TSSetMaxSteps(), TSSetExactFinalTime() 2995 @*/ 2996 PetscErrorCode TSSetMaxTime(TS ts,PetscReal maxtime) 2997 { 2998 PetscFunctionBegin; 2999 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3000 PetscValidLogicalCollectiveReal(ts,maxtime,2); 3001 ts->max_time = maxtime; 3002 PetscFunctionReturn(0); 3003 } 3004 3005 /*@ 3006 TSGetMaxTime - Gets the maximum (or final) time for timestepping. 3007 3008 Not Collective 3009 3010 Input Parameters: 3011 . ts - the TS context obtained from TSCreate() 3012 3013 Output Parameter: 3014 . maxtime - final time to step to 3015 3016 Level: advanced 3017 3018 .keywords: TS, timestep, get, maximum, time 3019 3020 .seealso: TSSetMaxTime(), TSGetMaxSteps(), TSSetMaxSteps() 3021 @*/ 3022 PetscErrorCode TSGetMaxTime(TS ts,PetscReal *maxtime) 3023 { 3024 PetscFunctionBegin; 3025 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3026 PetscValidRealPointer(maxtime,2); 3027 *maxtime = ts->max_time; 3028 PetscFunctionReturn(0); 3029 } 3030 3031 /*@ 3032 TSSetInitialTimeStep - Deprecated, use TSSetTime() and TSSetTimeStep(). 3033 3034 Level: deprecated 3035 3036 @*/ 3037 PetscErrorCode TSSetInitialTimeStep(TS ts,PetscReal initial_time,PetscReal time_step) 3038 { 3039 PetscErrorCode ierr; 3040 PetscFunctionBegin; 3041 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3042 ierr = TSSetTime(ts,initial_time);CHKERRQ(ierr); 3043 ierr = TSSetTimeStep(ts,time_step);CHKERRQ(ierr); 3044 PetscFunctionReturn(0); 3045 } 3046 3047 /*@ 3048 TSGetDuration - Deprecated, use TSGetMaxSteps() and TSGetMaxTime(). 3049 3050 Level: deprecated 3051 3052 @*/ 3053 PetscErrorCode TSGetDuration(TS ts, PetscInt *maxsteps, PetscReal *maxtime) 3054 { 3055 PetscFunctionBegin; 3056 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 3057 if (maxsteps) { 3058 PetscValidIntPointer(maxsteps,2); 3059 *maxsteps = ts->max_steps; 3060 } 3061 if (maxtime) { 3062 PetscValidScalarPointer(maxtime,3); 3063 *maxtime = ts->max_time; 3064 } 3065 PetscFunctionReturn(0); 3066 } 3067 3068 /*@ 3069 TSSetDuration - Deprecated, use TSSetMaxSteps() and TSSetMaxTime(). 3070 3071 Level: deprecated 3072 3073 @*/ 3074 PetscErrorCode TSSetDuration(TS ts,PetscInt maxsteps,PetscReal maxtime) 3075 { 3076 PetscFunctionBegin; 3077 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3078 PetscValidLogicalCollectiveInt(ts,maxsteps,2); 3079 PetscValidLogicalCollectiveReal(ts,maxtime,2); 3080 if (maxsteps >= 0) ts->max_steps = maxsteps; 3081 if (maxtime != PETSC_DEFAULT) ts->max_time = maxtime; 3082 PetscFunctionReturn(0); 3083 } 3084 3085 /*@ 3086 TSGetTimeStepNumber - Deprecated, use TSGetStepNumber(). 3087 3088 Level: deprecated 3089 3090 @*/ 3091 PetscErrorCode TSGetTimeStepNumber(TS ts,PetscInt *steps) { return TSGetStepNumber(ts,steps); } 3092 3093 /*@ 3094 TSGetTotalSteps - Deprecated, use TSGetStepNumber(). 3095 3096 Level: deprecated 3097 3098 @*/ 3099 PetscErrorCode TSGetTotalSteps(TS ts,PetscInt *steps) { return TSGetStepNumber(ts,steps); } 3100 3101 /*@ 3102 TSSetSolution - Sets the initial solution vector 3103 for use by the TS routines. 3104 3105 Logically Collective on TS and Vec 3106 3107 Input Parameters: 3108 + ts - the TS context obtained from TSCreate() 3109 - u - the solution vector 3110 3111 Level: beginner 3112 3113 .keywords: TS, timestep, set, solution, initial values 3114 @*/ 3115 PetscErrorCode TSSetSolution(TS ts,Vec u) 3116 { 3117 PetscErrorCode ierr; 3118 DM dm; 3119 3120 PetscFunctionBegin; 3121 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3122 PetscValidHeaderSpecific(u,VEC_CLASSID,2); 3123 ierr = PetscObjectReference((PetscObject)u);CHKERRQ(ierr); 3124 ierr = VecDestroy(&ts->vec_sol);CHKERRQ(ierr); 3125 ts->vec_sol = u; 3126 3127 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 3128 ierr = DMShellSetGlobalVector(dm,u);CHKERRQ(ierr); 3129 PetscFunctionReturn(0); 3130 } 3131 3132 /*@ 3133 TSAdjointSetSteps - Sets the number of steps the adjoint solver should take backward in time 3134 3135 Logically Collective on TS 3136 3137 Input Parameters: 3138 + ts - the TS context obtained from TSCreate() 3139 . steps - number of steps to use 3140 3141 Level: intermediate 3142 3143 Notes: Normally one does not call this and TSAdjointSolve() integrates back to the original timestep. One can call this 3144 so as to integrate back to less than the original timestep 3145 3146 .keywords: TS, timestep, set, maximum, iterations 3147 3148 .seealso: TSSetExactFinalTime() 3149 @*/ 3150 PetscErrorCode TSAdjointSetSteps(TS ts,PetscInt steps) 3151 { 3152 PetscFunctionBegin; 3153 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3154 PetscValidLogicalCollectiveInt(ts,steps,2); 3155 if (steps < 0) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_OUTOFRANGE,"Cannot step back a negative number of steps"); 3156 if (steps > ts->steps) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_OUTOFRANGE,"Cannot step back more than the total number of forward steps"); 3157 ts->adjoint_max_steps = steps; 3158 PetscFunctionReturn(0); 3159 } 3160 3161 /*@ 3162 TSSetCostGradients - Sets the initial value of the gradients of the cost function w.r.t. initial values and w.r.t. the problem parameters 3163 for use by the TSAdjoint routines. 3164 3165 Logically Collective on TS and Vec 3166 3167 Input Parameters: 3168 + ts - the TS context obtained from TSCreate() 3169 . lambda - gradients with respect to the initial condition variables, the dimension and parallel layout of these vectors is the same as the ODE solution vector 3170 - mu - gradients with respect to the parameters, the number of entries in these vectors is the same as the number of parameters 3171 3172 Level: beginner 3173 3174 Notes: the entries in these vectors must be correctly initialized with the values lamda_i = df/dy|finaltime mu_i = df/dp|finaltime 3175 3176 .keywords: TS, timestep, set, sensitivity, initial values 3177 @*/ 3178 PetscErrorCode TSSetCostGradients(TS ts,PetscInt numcost,Vec *lambda,Vec *mu) 3179 { 3180 PetscFunctionBegin; 3181 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3182 PetscValidPointer(lambda,2); 3183 ts->vecs_sensi = lambda; 3184 ts->vecs_sensip = mu; 3185 if (ts->numcost && ts->numcost!=numcost) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"The number of cost functions (2rd parameter of TSSetCostIntegrand()) is inconsistent with the one set by TSSetCostIntegrand"); 3186 ts->numcost = numcost; 3187 PetscFunctionReturn(0); 3188 } 3189 3190 /*@C 3191 TSAdjointSetRHSJacobian - Sets the function that computes the Jacobian of G w.r.t. the parameters p where y_t = G(y,p,t), as well as the location to store the matrix. 3192 3193 Logically Collective on TS 3194 3195 Input Parameters: 3196 + ts - The TS context obtained from TSCreate() 3197 - func - The function 3198 3199 Calling sequence of func: 3200 $ func (TS ts,PetscReal t,Vec y,Mat A,void *ctx); 3201 + t - current timestep 3202 . y - input vector (current ODE solution) 3203 . A - output matrix 3204 - ctx - [optional] user-defined function context 3205 3206 Level: intermediate 3207 3208 Notes: Amat has the same number of rows and the same row parallel layout as u, Amat has the same number of columns and parallel layout as p 3209 3210 .keywords: TS, sensitivity 3211 .seealso: 3212 @*/ 3213 PetscErrorCode TSAdjointSetRHSJacobian(TS ts,Mat Amat,PetscErrorCode (*func)(TS,PetscReal,Vec,Mat,void*),void *ctx) 3214 { 3215 PetscErrorCode ierr; 3216 3217 PetscFunctionBegin; 3218 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 3219 PetscValidHeaderSpecific(Amat,MAT_CLASSID,2); 3220 3221 ts->rhsjacobianp = func; 3222 ts->rhsjacobianpctx = ctx; 3223 if(Amat) { 3224 ierr = PetscObjectReference((PetscObject)Amat);CHKERRQ(ierr); 3225 ierr = MatDestroy(&ts->Jacp);CHKERRQ(ierr); 3226 ts->Jacp = Amat; 3227 } 3228 PetscFunctionReturn(0); 3229 } 3230 3231 /*@C 3232 TSAdjointComputeRHSJacobian - Runs the user-defined Jacobian function. 3233 3234 Collective on TS 3235 3236 Input Parameters: 3237 . ts - The TS context obtained from TSCreate() 3238 3239 Level: developer 3240 3241 .keywords: TS, sensitivity 3242 .seealso: TSAdjointSetRHSJacobian() 3243 @*/ 3244 PetscErrorCode TSAdjointComputeRHSJacobian(TS ts,PetscReal t,Vec X,Mat Amat) 3245 { 3246 PetscErrorCode ierr; 3247 3248 PetscFunctionBegin; 3249 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3250 PetscValidHeaderSpecific(X,VEC_CLASSID,3); 3251 PetscValidPointer(Amat,4); 3252 3253 PetscStackPush("TS user JacobianP function for sensitivity analysis"); 3254 ierr = (*ts->rhsjacobianp)(ts,t,X,Amat,ts->rhsjacobianpctx); CHKERRQ(ierr); 3255 PetscStackPop; 3256 PetscFunctionReturn(0); 3257 } 3258 3259 /*@C 3260 TSSetCostIntegrand - Sets the routine for evaluating the integral term in one or more cost functions 3261 3262 Logically Collective on TS 3263 3264 Input Parameters: 3265 + ts - the TS context obtained from TSCreate() 3266 . numcost - number of gradients to be computed, this is the number of cost functions 3267 . costintegral - vector that stores the integral values 3268 . rf - routine for evaluating the integrand function 3269 . drdyf - function that computes the gradients of the r's with respect to y,NULL if not a function y 3270 . drdpf - function that computes the gradients of the r's with respect to p, NULL if not a function of p 3271 . fwd - flag indicating whether to evaluate cost integral in the forward run or the adjoint run 3272 - ctx - [optional] user-defined context for private data for the function evaluation routine (may be NULL) 3273 3274 Calling sequence of rf: 3275 $ PetscErrorCode rf(TS ts,PetscReal t,Vec y,Vec f,void *ctx); 3276 3277 Calling sequence of drdyf: 3278 $ PetscErroCode drdyf(TS ts,PetscReal t,Vec y,Vec *drdy,void *ctx); 3279 3280 Calling sequence of drdpf: 3281 $ PetscErroCode drdpf(TS ts,PetscReal t,Vec y,Vec *drdp,void *ctx); 3282 3283 Level: intermediate 3284 3285 Notes: For optimization there is usually a single cost function (numcost = 1). For sensitivities there may be multiple cost functions 3286 3287 .keywords: TS, sensitivity analysis, timestep, set, quadrature, function 3288 3289 .seealso: TSAdjointSetRHSJacobian(),TSGetCostGradients(), TSSetCostGradients() 3290 @*/ 3291 PetscErrorCode TSSetCostIntegrand(TS ts,PetscInt numcost,Vec costintegral,PetscErrorCode (*rf)(TS,PetscReal,Vec,Vec,void*), 3292 PetscErrorCode (*drdyf)(TS,PetscReal,Vec,Vec*,void*), 3293 PetscErrorCode (*drdpf)(TS,PetscReal,Vec,Vec*,void*), 3294 PetscBool fwd,void *ctx) 3295 { 3296 PetscErrorCode ierr; 3297 3298 PetscFunctionBegin; 3299 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3300 if (costintegral) PetscValidHeaderSpecific(costintegral,VEC_CLASSID,3); 3301 if (ts->numcost && ts->numcost!=numcost) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"The number of cost functions (2rd parameter of TSSetCostIntegrand()) is inconsistent with the one set by TSSetCostGradients() or TSForwardSetIntegralGradients()"); 3302 if (!ts->numcost) ts->numcost=numcost; 3303 3304 if (costintegral) { 3305 ierr = PetscObjectReference((PetscObject)costintegral);CHKERRQ(ierr); 3306 ierr = VecDestroy(&ts->vec_costintegral);CHKERRQ(ierr); 3307 ts->vec_costintegral = costintegral; 3308 } else { 3309 if (!ts->vec_costintegral) { /* Create a seq vec if user does not provide one */ 3310 ierr = VecCreateSeq(PETSC_COMM_SELF,numcost,&ts->vec_costintegral);CHKERRQ(ierr); 3311 } else { 3312 ierr = VecSet(ts->vec_costintegral,0.0);CHKERRQ(ierr); 3313 } 3314 } 3315 if (!ts->vec_costintegrand) { 3316 ierr = VecDuplicate(ts->vec_costintegral,&ts->vec_costintegrand);CHKERRQ(ierr); 3317 } else { 3318 ierr = VecSet(ts->vec_costintegrand,0.0);CHKERRQ(ierr); 3319 } 3320 ts->costintegralfwd = fwd; /* Evaluate the cost integral in forward run if fwd is true */ 3321 ts->costintegrand = rf; 3322 ts->costintegrandctx = ctx; 3323 ts->drdyfunction = drdyf; 3324 ts->drdpfunction = drdpf; 3325 PetscFunctionReturn(0); 3326 } 3327 3328 /*@ 3329 TSGetCostIntegral - Returns the values of the integral term in the cost functions. 3330 It is valid to call the routine after a backward run. 3331 3332 Not Collective 3333 3334 Input Parameter: 3335 . ts - the TS context obtained from TSCreate() 3336 3337 Output Parameter: 3338 . v - the vector containing the integrals for each cost function 3339 3340 Level: intermediate 3341 3342 .seealso: TSSetCostIntegrand() 3343 3344 .keywords: TS, sensitivity analysis 3345 @*/ 3346 PetscErrorCode TSGetCostIntegral(TS ts,Vec *v) 3347 { 3348 PetscFunctionBegin; 3349 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3350 PetscValidPointer(v,2); 3351 *v = ts->vec_costintegral; 3352 PetscFunctionReturn(0); 3353 } 3354 3355 /*@ 3356 TSComputeCostIntegrand - Evaluates the integral function in the cost functions. 3357 3358 Input Parameters: 3359 + ts - the TS context 3360 . t - current time 3361 - y - state vector, i.e. current solution 3362 3363 Output Parameter: 3364 . q - vector of size numcost to hold the outputs 3365 3366 Note: 3367 Most users should not need to explicitly call this routine, as it 3368 is used internally within the sensitivity analysis context. 3369 3370 Level: developer 3371 3372 .keywords: TS, compute 3373 3374 .seealso: TSSetCostIntegrand() 3375 @*/ 3376 PetscErrorCode TSComputeCostIntegrand(TS ts,PetscReal t,Vec y,Vec q) 3377 { 3378 PetscErrorCode ierr; 3379 3380 PetscFunctionBegin; 3381 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3382 PetscValidHeaderSpecific(y,VEC_CLASSID,3); 3383 PetscValidHeaderSpecific(q,VEC_CLASSID,4); 3384 3385 ierr = PetscLogEventBegin(TS_FunctionEval,ts,y,q,0);CHKERRQ(ierr); 3386 if (ts->costintegrand) { 3387 PetscStackPush("TS user integrand in the cost function"); 3388 ierr = (*ts->costintegrand)(ts,t,y,q,ts->costintegrandctx);CHKERRQ(ierr); 3389 PetscStackPop; 3390 } else { 3391 ierr = VecZeroEntries(q);CHKERRQ(ierr); 3392 } 3393 3394 ierr = PetscLogEventEnd(TS_FunctionEval,ts,y,q,0);CHKERRQ(ierr); 3395 PetscFunctionReturn(0); 3396 } 3397 3398 /*@ 3399 TSAdjointComputeDRDYFunction - Runs the user-defined DRDY function. 3400 3401 Collective on TS 3402 3403 Input Parameters: 3404 . ts - The TS context obtained from TSCreate() 3405 3406 Notes: 3407 TSAdjointComputeDRDYFunction() is typically used for sensitivity implementation, 3408 so most users would not generally call this routine themselves. 3409 3410 Level: developer 3411 3412 .keywords: TS, sensitivity 3413 .seealso: TSAdjointComputeDRDYFunction() 3414 @*/ 3415 PetscErrorCode TSAdjointComputeDRDYFunction(TS ts,PetscReal t,Vec y,Vec *drdy) 3416 { 3417 PetscErrorCode ierr; 3418 3419 PetscFunctionBegin; 3420 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3421 PetscValidHeaderSpecific(y,VEC_CLASSID,3); 3422 3423 PetscStackPush("TS user DRDY function for sensitivity analysis"); 3424 ierr = (*ts->drdyfunction)(ts,t,y,drdy,ts->costintegrandctx); CHKERRQ(ierr); 3425 PetscStackPop; 3426 PetscFunctionReturn(0); 3427 } 3428 3429 /*@ 3430 TSAdjointComputeDRDPFunction - Runs the user-defined DRDP function. 3431 3432 Collective on TS 3433 3434 Input Parameters: 3435 . ts - The TS context obtained from TSCreate() 3436 3437 Notes: 3438 TSDRDPFunction() is typically used for sensitivity implementation, 3439 so most users would not generally call this routine themselves. 3440 3441 Level: developer 3442 3443 .keywords: TS, sensitivity 3444 .seealso: TSAdjointSetDRDPFunction() 3445 @*/ 3446 PetscErrorCode TSAdjointComputeDRDPFunction(TS ts,PetscReal t,Vec y,Vec *drdp) 3447 { 3448 PetscErrorCode ierr; 3449 3450 PetscFunctionBegin; 3451 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3452 PetscValidHeaderSpecific(y,VEC_CLASSID,3); 3453 3454 PetscStackPush("TS user DRDP function for sensitivity analysis"); 3455 ierr = (*ts->drdpfunction)(ts,t,y,drdp,ts->costintegrandctx); CHKERRQ(ierr); 3456 PetscStackPop; 3457 PetscFunctionReturn(0); 3458 } 3459 3460 /*@C 3461 TSSetPreStep - Sets the general-purpose function 3462 called once at the beginning of each time step. 3463 3464 Logically Collective on TS 3465 3466 Input Parameters: 3467 + ts - The TS context obtained from TSCreate() 3468 - func - The function 3469 3470 Calling sequence of func: 3471 . func (TS ts); 3472 3473 Level: intermediate 3474 3475 .keywords: TS, timestep 3476 .seealso: TSSetPreStage(), TSSetPostStage(), TSSetPostStep(), TSStep(), TSRestartStep() 3477 @*/ 3478 PetscErrorCode TSSetPreStep(TS ts, PetscErrorCode (*func)(TS)) 3479 { 3480 PetscFunctionBegin; 3481 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 3482 ts->prestep = func; 3483 PetscFunctionReturn(0); 3484 } 3485 3486 /*@ 3487 TSPreStep - Runs the user-defined pre-step function. 3488 3489 Collective on TS 3490 3491 Input Parameters: 3492 . ts - The TS context obtained from TSCreate() 3493 3494 Notes: 3495 TSPreStep() is typically used within time stepping implementations, 3496 so most users would not generally call this routine themselves. 3497 3498 Level: developer 3499 3500 .keywords: TS, timestep 3501 .seealso: TSSetPreStep(), TSPreStage(), TSPostStage(), TSPostStep() 3502 @*/ 3503 PetscErrorCode TSPreStep(TS ts) 3504 { 3505 PetscErrorCode ierr; 3506 3507 PetscFunctionBegin; 3508 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3509 if (ts->prestep) { 3510 Vec U; 3511 PetscObjectState sprev,spost; 3512 3513 ierr = TSGetSolution(ts,&U);CHKERRQ(ierr); 3514 ierr = PetscObjectStateGet((PetscObject)U,&sprev);CHKERRQ(ierr); 3515 PetscStackCallStandard((*ts->prestep),(ts)); 3516 ierr = PetscObjectStateGet((PetscObject)U,&spost);CHKERRQ(ierr); 3517 if (sprev != spost) {ierr = TSRestartStep(ts);CHKERRQ(ierr);} 3518 } 3519 PetscFunctionReturn(0); 3520 } 3521 3522 /*@C 3523 TSSetPreStage - Sets the general-purpose function 3524 called once at the beginning of each stage. 3525 3526 Logically Collective on TS 3527 3528 Input Parameters: 3529 + ts - The TS context obtained from TSCreate() 3530 - func - The function 3531 3532 Calling sequence of func: 3533 . PetscErrorCode func(TS ts, PetscReal stagetime); 3534 3535 Level: intermediate 3536 3537 Note: 3538 There may be several stages per time step. If the solve for a given stage fails, the step may be rejected and retried. 3539 The time step number being computed can be queried using TSGetStepNumber() and the total size of the step being 3540 attempted can be obtained using TSGetTimeStep(). The time at the start of the step is available via TSGetTime(). 3541 3542 .keywords: TS, timestep 3543 .seealso: TSSetPostStage(), TSSetPreStep(), TSSetPostStep(), TSGetApplicationContext() 3544 @*/ 3545 PetscErrorCode TSSetPreStage(TS ts, PetscErrorCode (*func)(TS,PetscReal)) 3546 { 3547 PetscFunctionBegin; 3548 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 3549 ts->prestage = func; 3550 PetscFunctionReturn(0); 3551 } 3552 3553 /*@C 3554 TSSetPostStage - Sets the general-purpose function 3555 called once at the end of each stage. 3556 3557 Logically Collective on TS 3558 3559 Input Parameters: 3560 + ts - The TS context obtained from TSCreate() 3561 - func - The function 3562 3563 Calling sequence of func: 3564 . PetscErrorCode func(TS ts, PetscReal stagetime, PetscInt stageindex, Vec* Y); 3565 3566 Level: intermediate 3567 3568 Note: 3569 There may be several stages per time step. If the solve for a given stage fails, the step may be rejected and retried. 3570 The time step number being computed can be queried using TSGetStepNumber() and the total size of the step being 3571 attempted can be obtained using TSGetTimeStep(). The time at the start of the step is available via TSGetTime(). 3572 3573 .keywords: TS, timestep 3574 .seealso: TSSetPreStage(), TSSetPreStep(), TSSetPostStep(), TSGetApplicationContext() 3575 @*/ 3576 PetscErrorCode TSSetPostStage(TS ts, PetscErrorCode (*func)(TS,PetscReal,PetscInt,Vec*)) 3577 { 3578 PetscFunctionBegin; 3579 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 3580 ts->poststage = func; 3581 PetscFunctionReturn(0); 3582 } 3583 3584 /*@C 3585 TSSetPostEvaluate - Sets the general-purpose function 3586 called once at the end of each step evaluation. 3587 3588 Logically Collective on TS 3589 3590 Input Parameters: 3591 + ts - The TS context obtained from TSCreate() 3592 - func - The function 3593 3594 Calling sequence of func: 3595 . PetscErrorCode func(TS ts); 3596 3597 Level: intermediate 3598 3599 Note: 3600 Semantically, TSSetPostEvaluate() differs from TSSetPostStep() since the function it sets is called before event-handling 3601 thus guaranteeing the same solution (computed by the time-stepper) will be passed to it. On the other hand, TSPostStep() 3602 may be passed a different solution, possibly changed by the event handler. TSPostEvaluate() is called after the next step 3603 solution is evaluated allowing to modify it, if need be. The solution can be obtained with TSGetSolution(), the time step 3604 with TSGetTimeStep(), and the time at the start of the step is available via TSGetTime() 3605 3606 .keywords: TS, timestep 3607 .seealso: TSSetPreStage(), TSSetPreStep(), TSSetPostStep(), TSGetApplicationContext() 3608 @*/ 3609 PetscErrorCode TSSetPostEvaluate(TS ts, PetscErrorCode (*func)(TS)) 3610 { 3611 PetscFunctionBegin; 3612 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 3613 ts->postevaluate = func; 3614 PetscFunctionReturn(0); 3615 } 3616 3617 /*@ 3618 TSPreStage - Runs the user-defined pre-stage function set using TSSetPreStage() 3619 3620 Collective on TS 3621 3622 Input Parameters: 3623 . ts - The TS context obtained from TSCreate() 3624 stagetime - The absolute time of the current stage 3625 3626 Notes: 3627 TSPreStage() is typically used within time stepping implementations, 3628 most users would not generally call this routine themselves. 3629 3630 Level: developer 3631 3632 .keywords: TS, timestep 3633 .seealso: TSPostStage(), TSSetPreStep(), TSPreStep(), TSPostStep() 3634 @*/ 3635 PetscErrorCode TSPreStage(TS ts, PetscReal stagetime) 3636 { 3637 PetscErrorCode ierr; 3638 3639 PetscFunctionBegin; 3640 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3641 if (ts->prestage) { 3642 PetscStackCallStandard((*ts->prestage),(ts,stagetime)); 3643 } 3644 PetscFunctionReturn(0); 3645 } 3646 3647 /*@ 3648 TSPostStage - Runs the user-defined post-stage function set using TSSetPostStage() 3649 3650 Collective on TS 3651 3652 Input Parameters: 3653 . ts - The TS context obtained from TSCreate() 3654 stagetime - The absolute time of the current stage 3655 stageindex - Stage number 3656 Y - Array of vectors (of size = total number 3657 of stages) with the stage solutions 3658 3659 Notes: 3660 TSPostStage() is typically used within time stepping implementations, 3661 most users would not generally call this routine themselves. 3662 3663 Level: developer 3664 3665 .keywords: TS, timestep 3666 .seealso: TSPreStage(), TSSetPreStep(), TSPreStep(), TSPostStep() 3667 @*/ 3668 PetscErrorCode TSPostStage(TS ts, PetscReal stagetime, PetscInt stageindex, Vec *Y) 3669 { 3670 PetscErrorCode ierr; 3671 3672 PetscFunctionBegin; 3673 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3674 if (ts->poststage) { 3675 PetscStackCallStandard((*ts->poststage),(ts,stagetime,stageindex,Y)); 3676 } 3677 PetscFunctionReturn(0); 3678 } 3679 3680 /*@ 3681 TSPostEvaluate - Runs the user-defined post-evaluate function set using TSSetPostEvaluate() 3682 3683 Collective on TS 3684 3685 Input Parameters: 3686 . ts - The TS context obtained from TSCreate() 3687 3688 Notes: 3689 TSPostEvaluate() is typically used within time stepping implementations, 3690 most users would not generally call this routine themselves. 3691 3692 Level: developer 3693 3694 .keywords: TS, timestep 3695 .seealso: TSSetPostEvaluate(), TSSetPreStep(), TSPreStep(), TSPostStep() 3696 @*/ 3697 PetscErrorCode TSPostEvaluate(TS ts) 3698 { 3699 PetscErrorCode ierr; 3700 3701 PetscFunctionBegin; 3702 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3703 if (ts->postevaluate) { 3704 Vec U; 3705 PetscObjectState sprev,spost; 3706 3707 ierr = TSGetSolution(ts,&U);CHKERRQ(ierr); 3708 ierr = PetscObjectStateGet((PetscObject)U,&sprev);CHKERRQ(ierr); 3709 PetscStackCallStandard((*ts->postevaluate),(ts)); 3710 ierr = PetscObjectStateGet((PetscObject)U,&spost);CHKERRQ(ierr); 3711 if (sprev != spost) {ierr = TSRestartStep(ts);CHKERRQ(ierr);} 3712 } 3713 PetscFunctionReturn(0); 3714 } 3715 3716 /*@C 3717 TSSetPostStep - Sets the general-purpose function 3718 called once at the end of each time step. 3719 3720 Logically Collective on TS 3721 3722 Input Parameters: 3723 + ts - The TS context obtained from TSCreate() 3724 - func - The function 3725 3726 Calling sequence of func: 3727 $ func (TS ts); 3728 3729 Notes: 3730 The function set by TSSetPostStep() is called after each successful step. The solution vector X 3731 obtained by TSGetSolution() may be different than that computed at the step end if the event handler 3732 locates an event and TSPostEvent() modifies it. Use TSSetPostEvaluate() if an unmodified solution is needed instead. 3733 3734 Level: intermediate 3735 3736 .keywords: TS, timestep 3737 .seealso: TSSetPreStep(), TSSetPreStage(), TSSetPostEvaluate(), TSGetTimeStep(), TSGetStepNumber(), TSGetTime(), TSRestartStep() 3738 @*/ 3739 PetscErrorCode TSSetPostStep(TS ts, PetscErrorCode (*func)(TS)) 3740 { 3741 PetscFunctionBegin; 3742 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 3743 ts->poststep = func; 3744 PetscFunctionReturn(0); 3745 } 3746 3747 /*@ 3748 TSPostStep - Runs the user-defined post-step function. 3749 3750 Collective on TS 3751 3752 Input Parameters: 3753 . ts - The TS context obtained from TSCreate() 3754 3755 Notes: 3756 TSPostStep() is typically used within time stepping implementations, 3757 so most users would not generally call this routine themselves. 3758 3759 Level: developer 3760 3761 .keywords: TS, timestep 3762 @*/ 3763 PetscErrorCode TSPostStep(TS ts) 3764 { 3765 PetscErrorCode ierr; 3766 3767 PetscFunctionBegin; 3768 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3769 if (ts->poststep) { 3770 Vec U; 3771 PetscObjectState sprev,spost; 3772 3773 ierr = TSGetSolution(ts,&U);CHKERRQ(ierr); 3774 ierr = PetscObjectStateGet((PetscObject)U,&sprev);CHKERRQ(ierr); 3775 PetscStackCallStandard((*ts->poststep),(ts)); 3776 ierr = PetscObjectStateGet((PetscObject)U,&spost);CHKERRQ(ierr); 3777 if (sprev != spost) {ierr = TSRestartStep(ts);CHKERRQ(ierr);} 3778 } 3779 PetscFunctionReturn(0); 3780 } 3781 3782 /* ------------ Routines to set performance monitoring options ----------- */ 3783 3784 /*@C 3785 TSMonitorSet - Sets an ADDITIONAL function that is to be used at every 3786 timestep to display the iteration's progress. 3787 3788 Logically Collective on TS 3789 3790 Input Parameters: 3791 + ts - the TS context obtained from TSCreate() 3792 . monitor - monitoring routine 3793 . mctx - [optional] user-defined context for private data for the 3794 monitor routine (use NULL if no context is desired) 3795 - monitordestroy - [optional] routine that frees monitor context 3796 (may be NULL) 3797 3798 Calling sequence of monitor: 3799 $ PetscErrorCode monitor(TS ts,PetscInt steps,PetscReal time,Vec u,void *mctx) 3800 3801 + ts - the TS context 3802 . steps - iteration number (after the final time step the monitor routine may be called with a step of -1, this indicates the solution has been interpolated to this time) 3803 . time - current time 3804 . u - current iterate 3805 - mctx - [optional] monitoring context 3806 3807 Notes: 3808 This routine adds an additional monitor to the list of monitors that 3809 already has been loaded. 3810 3811 Fortran notes: Only a single monitor function can be set for each TS object 3812 3813 Level: intermediate 3814 3815 .keywords: TS, timestep, set, monitor 3816 3817 .seealso: TSMonitorDefault(), TSMonitorCancel() 3818 @*/ 3819 PetscErrorCode TSMonitorSet(TS ts,PetscErrorCode (*monitor)(TS,PetscInt,PetscReal,Vec,void*),void *mctx,PetscErrorCode (*mdestroy)(void**)) 3820 { 3821 PetscErrorCode ierr; 3822 PetscInt i; 3823 PetscBool identical; 3824 3825 PetscFunctionBegin; 3826 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3827 for (i=0; i<ts->numbermonitors;i++) { 3828 ierr = PetscMonitorCompare((PetscErrorCode (*)(void))monitor,mctx,mdestroy,(PetscErrorCode (*)(void))ts->monitor[i],ts->monitorcontext[i],ts->monitordestroy[i],&identical);CHKERRQ(ierr); 3829 if (identical) PetscFunctionReturn(0); 3830 } 3831 if (ts->numbermonitors >= MAXTSMONITORS) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Too many monitors set"); 3832 ts->monitor[ts->numbermonitors] = monitor; 3833 ts->monitordestroy[ts->numbermonitors] = mdestroy; 3834 ts->monitorcontext[ts->numbermonitors++] = (void*)mctx; 3835 PetscFunctionReturn(0); 3836 } 3837 3838 /*@C 3839 TSMonitorCancel - Clears all the monitors that have been set on a time-step object. 3840 3841 Logically Collective on TS 3842 3843 Input Parameters: 3844 . ts - the TS context obtained from TSCreate() 3845 3846 Notes: 3847 There is no way to remove a single, specific monitor. 3848 3849 Level: intermediate 3850 3851 .keywords: TS, timestep, set, monitor 3852 3853 .seealso: TSMonitorDefault(), TSMonitorSet() 3854 @*/ 3855 PetscErrorCode TSMonitorCancel(TS ts) 3856 { 3857 PetscErrorCode ierr; 3858 PetscInt i; 3859 3860 PetscFunctionBegin; 3861 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3862 for (i=0; i<ts->numbermonitors; i++) { 3863 if (ts->monitordestroy[i]) { 3864 ierr = (*ts->monitordestroy[i])(&ts->monitorcontext[i]);CHKERRQ(ierr); 3865 } 3866 } 3867 ts->numbermonitors = 0; 3868 PetscFunctionReturn(0); 3869 } 3870 3871 /*@C 3872 TSMonitorDefault - The Default monitor, prints the timestep and time for each step 3873 3874 Level: intermediate 3875 3876 .keywords: TS, set, monitor 3877 3878 .seealso: TSMonitorSet() 3879 @*/ 3880 PetscErrorCode TSMonitorDefault(TS ts,PetscInt step,PetscReal ptime,Vec v,PetscViewerAndFormat *vf) 3881 { 3882 PetscErrorCode ierr; 3883 PetscViewer viewer = vf->viewer; 3884 PetscBool iascii,ibinary; 3885 3886 PetscFunctionBegin; 3887 PetscValidHeaderSpecific(viewer,PETSC_VIEWER_CLASSID,4); 3888 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 3889 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&ibinary);CHKERRQ(ierr); 3890 ierr = PetscViewerPushFormat(viewer,vf->format);CHKERRQ(ierr); 3891 if (iascii) { 3892 ierr = PetscViewerASCIIAddTab(viewer,((PetscObject)ts)->tablevel);CHKERRQ(ierr); 3893 if (step == -1){ /* this indicates it is an interpolated solution */ 3894 ierr = PetscViewerASCIIPrintf(viewer,"Interpolated solution at time %g between steps %D and %D\n",(double)ptime,ts->steps-1,ts->steps);CHKERRQ(ierr); 3895 } else { 3896 ierr = PetscViewerASCIIPrintf(viewer,"%D TS dt %g time %g%s",step,(double)ts->time_step,(double)ptime,ts->steprollback ? " (r)\n" : "\n");CHKERRQ(ierr); 3897 } 3898 ierr = PetscViewerASCIISubtractTab(viewer,((PetscObject)ts)->tablevel);CHKERRQ(ierr); 3899 } else if (ibinary) { 3900 PetscMPIInt rank; 3901 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)viewer),&rank);CHKERRQ(ierr); 3902 if (!rank) { 3903 PetscBool skipHeader; 3904 PetscInt classid = REAL_FILE_CLASSID; 3905 3906 ierr = PetscViewerBinaryGetSkipHeader(viewer,&skipHeader);CHKERRQ(ierr); 3907 if (!skipHeader) { 3908 ierr = PetscViewerBinaryWrite(viewer,&classid,1,PETSC_INT,PETSC_FALSE);CHKERRQ(ierr); 3909 } 3910 ierr = PetscRealView(1,&ptime,viewer);CHKERRQ(ierr); 3911 } else { 3912 ierr = PetscRealView(0,&ptime,viewer);CHKERRQ(ierr); 3913 } 3914 } 3915 ierr = PetscViewerPopFormat(viewer);CHKERRQ(ierr); 3916 PetscFunctionReturn(0); 3917 } 3918 3919 /*@C 3920 TSAdjointMonitorSet - Sets an ADDITIONAL function that is to be used at every 3921 timestep to display the iteration's progress. 3922 3923 Logically Collective on TS 3924 3925 Input Parameters: 3926 + ts - the TS context obtained from TSCreate() 3927 . adjointmonitor - monitoring routine 3928 . adjointmctx - [optional] user-defined context for private data for the 3929 monitor routine (use NULL if no context is desired) 3930 - adjointmonitordestroy - [optional] routine that frees monitor context 3931 (may be NULL) 3932 3933 Calling sequence of monitor: 3934 $ int adjointmonitor(TS ts,PetscInt steps,PetscReal time,Vec u,PetscInt numcost,Vec *lambda, Vec *mu,void *adjointmctx) 3935 3936 + ts - the TS context 3937 . steps - iteration number (after the final time step the monitor routine is called with a step of -1, this is at the final time which may have 3938 been interpolated to) 3939 . time - current time 3940 . u - current iterate 3941 . numcost - number of cost functionos 3942 . lambda - sensitivities to initial conditions 3943 . mu - sensitivities to parameters 3944 - adjointmctx - [optional] adjoint monitoring context 3945 3946 Notes: 3947 This routine adds an additional monitor to the list of monitors that 3948 already has been loaded. 3949 3950 Fortran notes: Only a single monitor function can be set for each TS object 3951 3952 Level: intermediate 3953 3954 .keywords: TS, timestep, set, adjoint, monitor 3955 3956 .seealso: TSAdjointMonitorCancel() 3957 @*/ 3958 PetscErrorCode TSAdjointMonitorSet(TS ts,PetscErrorCode (*adjointmonitor)(TS,PetscInt,PetscReal,Vec,PetscInt,Vec*,Vec*,void*),void *adjointmctx,PetscErrorCode (*adjointmdestroy)(void**)) 3959 { 3960 PetscErrorCode ierr; 3961 PetscInt i; 3962 PetscBool identical; 3963 3964 PetscFunctionBegin; 3965 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3966 for (i=0; i<ts->numbermonitors;i++) { 3967 ierr = PetscMonitorCompare((PetscErrorCode (*)(void))adjointmonitor,adjointmctx,adjointmdestroy,(PetscErrorCode (*)(void))ts->adjointmonitor[i],ts->adjointmonitorcontext[i],ts->adjointmonitordestroy[i],&identical);CHKERRQ(ierr); 3968 if (identical) PetscFunctionReturn(0); 3969 } 3970 if (ts->numberadjointmonitors >= MAXTSMONITORS) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Too many adjoint monitors set"); 3971 ts->adjointmonitor[ts->numberadjointmonitors] = adjointmonitor; 3972 ts->adjointmonitordestroy[ts->numberadjointmonitors] = adjointmdestroy; 3973 ts->adjointmonitorcontext[ts->numberadjointmonitors++] = (void*)adjointmctx; 3974 PetscFunctionReturn(0); 3975 } 3976 3977 /*@C 3978 TSAdjointMonitorCancel - Clears all the adjoint monitors that have been set on a time-step object. 3979 3980 Logically Collective on TS 3981 3982 Input Parameters: 3983 . ts - the TS context obtained from TSCreate() 3984 3985 Notes: 3986 There is no way to remove a single, specific monitor. 3987 3988 Level: intermediate 3989 3990 .keywords: TS, timestep, set, adjoint, monitor 3991 3992 .seealso: TSAdjointMonitorSet() 3993 @*/ 3994 PetscErrorCode TSAdjointMonitorCancel(TS ts) 3995 { 3996 PetscErrorCode ierr; 3997 PetscInt i; 3998 3999 PetscFunctionBegin; 4000 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4001 for (i=0; i<ts->numberadjointmonitors; i++) { 4002 if (ts->adjointmonitordestroy[i]) { 4003 ierr = (*ts->adjointmonitordestroy[i])(&ts->adjointmonitorcontext[i]);CHKERRQ(ierr); 4004 } 4005 } 4006 ts->numberadjointmonitors = 0; 4007 PetscFunctionReturn(0); 4008 } 4009 4010 /*@C 4011 TSAdjointMonitorDefault - the default monitor of adjoint computations 4012 4013 Level: intermediate 4014 4015 .keywords: TS, set, monitor 4016 4017 .seealso: TSAdjointMonitorSet() 4018 @*/ 4019 PetscErrorCode TSAdjointMonitorDefault(TS ts,PetscInt step,PetscReal ptime,Vec v,PetscInt numcost,Vec *lambda,Vec *mu,PetscViewerAndFormat *vf) 4020 { 4021 PetscErrorCode ierr; 4022 PetscViewer viewer = vf->viewer; 4023 4024 PetscFunctionBegin; 4025 PetscValidHeaderSpecific(viewer,PETSC_VIEWER_CLASSID,4); 4026 ierr = PetscViewerPushFormat(viewer,vf->format);CHKERRQ(ierr); 4027 ierr = PetscViewerASCIIAddTab(viewer,((PetscObject)ts)->tablevel);CHKERRQ(ierr); 4028 ierr = PetscViewerASCIIPrintf(viewer,"%D TS dt %g time %g%s",step,(double)ts->time_step,(double)ptime,ts->steprollback ? " (r)\n" : "\n");CHKERRQ(ierr); 4029 ierr = PetscViewerASCIISubtractTab(viewer,((PetscObject)ts)->tablevel);CHKERRQ(ierr); 4030 ierr = PetscViewerPopFormat(viewer);CHKERRQ(ierr); 4031 PetscFunctionReturn(0); 4032 } 4033 4034 /*@ 4035 TSInterpolate - Interpolate the solution computed during the previous step to an arbitrary location in the interval 4036 4037 Collective on TS 4038 4039 Input Argument: 4040 + ts - time stepping context 4041 - t - time to interpolate to 4042 4043 Output Argument: 4044 . U - state at given time 4045 4046 Level: intermediate 4047 4048 Developer Notes: 4049 TSInterpolate() and the storing of previous steps/stages should be generalized to support delay differential equations and continuous adjoints. 4050 4051 .keywords: TS, set 4052 4053 .seealso: TSSetExactFinalTime(), TSSolve() 4054 @*/ 4055 PetscErrorCode TSInterpolate(TS ts,PetscReal t,Vec U) 4056 { 4057 PetscErrorCode ierr; 4058 4059 PetscFunctionBegin; 4060 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4061 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 4062 if (t < ts->ptime_prev || t > ts->ptime) SETERRQ3(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_OUTOFRANGE,"Requested time %g not in last time steps [%g,%g]",t,(double)ts->ptime_prev,(double)ts->ptime); 4063 if (!ts->ops->interpolate) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"%s does not provide interpolation",((PetscObject)ts)->type_name); 4064 ierr = (*ts->ops->interpolate)(ts,t,U);CHKERRQ(ierr); 4065 PetscFunctionReturn(0); 4066 } 4067 4068 /*@ 4069 TSStep - Steps one time step 4070 4071 Collective on TS 4072 4073 Input Parameter: 4074 . ts - the TS context obtained from TSCreate() 4075 4076 Level: developer 4077 4078 Notes: 4079 The public interface for the ODE/DAE solvers is TSSolve(), you should almost for sure be using that routine and not this routine. 4080 4081 The hook set using TSSetPreStep() is called before each attempt to take the step. In general, the time step size may 4082 be changed due to adaptive error controller or solve failures. Note that steps may contain multiple stages. 4083 4084 This may over-step the final time provided in TSSetMaxTime() depending on the time-step used. TSSolve() interpolates to exactly the 4085 time provided in TSSetMaxTime(). One can use TSInterpolate() to determine an interpolated solution within the final timestep. 4086 4087 .keywords: TS, timestep, solve 4088 4089 .seealso: TSCreate(), TSSetUp(), TSDestroy(), TSSolve(), TSSetPreStep(), TSSetPreStage(), TSSetPostStage(), TSInterpolate() 4090 @*/ 4091 PetscErrorCode TSStep(TS ts) 4092 { 4093 PetscErrorCode ierr; 4094 static PetscBool cite = PETSC_FALSE; 4095 PetscReal ptime; 4096 4097 PetscFunctionBegin; 4098 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4099 ierr = PetscCitationsRegister("@techreport{tspaper,\n" 4100 " title = {{PETSc/TS}: A Modern Scalable {DAE/ODE} Solver Library},\n" 4101 " author = {Shrirang Abhyankar and Jed Brown and Emil Constantinescu and Debojyoti Ghosh and Barry F. Smith},\n" 4102 " type = {Preprint},\n" 4103 " number = {ANL/MCS-P5061-0114},\n" 4104 " institution = {Argonne National Laboratory},\n" 4105 " year = {2014}\n}\n",&cite);CHKERRQ(ierr); 4106 4107 ierr = TSSetUp(ts);CHKERRQ(ierr); 4108 ierr = TSTrajectorySetUp(ts->trajectory,ts);CHKERRQ(ierr); 4109 4110 if (ts->max_time >= PETSC_MAX_REAL && ts->max_steps == PETSC_MAX_INT) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONGSTATE,"You must call TSSetMaxTime() or TSSetMaxSteps(), or use -ts_max_time <time> or -ts_max_steps <steps>"); 4111 if (ts->exact_final_time == TS_EXACTFINALTIME_UNSPECIFIED) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONGSTATE,"You must call TSSetExactFinalTime() or use -ts_exact_final_time <stepover,interpolate,matchstep> before calling TSStep()"); 4112 if (ts->exact_final_time == TS_EXACTFINALTIME_MATCHSTEP && !ts->adapt) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Since TS is not adaptive you cannot use TS_EXACTFINALTIME_MATCHSTEP, suggest TS_EXACTFINALTIME_INTERPOLATE"); 4113 4114 if (!ts->steps) ts->ptime_prev = ts->ptime; 4115 ptime = ts->ptime; ts->ptime_prev_rollback = ts->ptime_prev; 4116 ts->reason = TS_CONVERGED_ITERATING; 4117 if (!ts->ops->step) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"TSStep not implemented for type '%s'",((PetscObject)ts)->type_name); 4118 ierr = PetscLogEventBegin(TS_Step,ts,0,0,0);CHKERRQ(ierr); 4119 ierr = (*ts->ops->step)(ts);CHKERRQ(ierr); 4120 ierr = PetscLogEventEnd(TS_Step,ts,0,0,0);CHKERRQ(ierr); 4121 ts->ptime_prev = ptime; 4122 ts->steps++; 4123 ts->steprollback = PETSC_FALSE; 4124 ts->steprestart = PETSC_FALSE; 4125 4126 if (ts->reason < 0) { 4127 if (ts->errorifstepfailed) { 4128 if (ts->reason == TS_DIVERGED_NONLINEAR_SOLVE) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_NOT_CONVERGED,"TSStep has failed due to %s, increase -ts_max_snes_failures or make negative to attempt recovery",TSConvergedReasons[ts->reason]); 4129 else SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_NOT_CONVERGED,"TSStep has failed due to %s",TSConvergedReasons[ts->reason]); 4130 } 4131 } else if (!ts->reason) { 4132 if (ts->steps >= ts->max_steps) ts->reason = TS_CONVERGED_ITS; 4133 else if (ts->ptime >= ts->max_time) ts->reason = TS_CONVERGED_TIME; 4134 } 4135 PetscFunctionReturn(0); 4136 } 4137 4138 /*@ 4139 TSAdjointStep - Steps one time step backward in the adjoint run 4140 4141 Collective on TS 4142 4143 Input Parameter: 4144 . ts - the TS context obtained from TSCreate() 4145 4146 Level: intermediate 4147 4148 .keywords: TS, adjoint, step 4149 4150 .seealso: TSAdjointSetUp(), TSAdjointSolve() 4151 @*/ 4152 PetscErrorCode TSAdjointStep(TS ts) 4153 { 4154 DM dm; 4155 PetscErrorCode ierr; 4156 4157 PetscFunctionBegin; 4158 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4159 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 4160 ierr = TSAdjointSetUp(ts);CHKERRQ(ierr); 4161 4162 ierr = VecViewFromOptions(ts->vec_sol,(PetscObject)ts,"-ts_view_solution");CHKERRQ(ierr); 4163 4164 ts->reason = TS_CONVERGED_ITERATING; 4165 ts->ptime_prev = ts->ptime; 4166 if (!ts->ops->adjointstep) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_NOT_CONVERGED,"TSStep has failed because the adjoint of %s has not been implemented, try other time stepping methods for adjoint sensitivity analysis",((PetscObject)ts)->type_name); 4167 ierr = PetscLogEventBegin(TS_AdjointStep,ts,0,0,0);CHKERRQ(ierr); 4168 ierr = (*ts->ops->adjointstep)(ts);CHKERRQ(ierr); 4169 ierr = PetscLogEventEnd(TS_AdjointStep,ts,0,0,0);CHKERRQ(ierr); 4170 ts->adjoint_steps++; ts->steps--; 4171 4172 if (ts->reason < 0) { 4173 if (ts->errorifstepfailed) { 4174 if (ts->reason == TS_DIVERGED_NONLINEAR_SOLVE) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_NOT_CONVERGED,"TSStep has failed due to %s, increase -ts_max_snes_failures or make negative to attempt recovery",TSConvergedReasons[ts->reason]); 4175 else if (ts->reason == TS_DIVERGED_STEP_REJECTED) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_NOT_CONVERGED,"TSStep has failed due to %s, increase -ts_max_reject or make negative to attempt recovery",TSConvergedReasons[ts->reason]); 4176 else SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_NOT_CONVERGED,"TSStep has failed due to %s",TSConvergedReasons[ts->reason]); 4177 } 4178 } else if (!ts->reason) { 4179 if (ts->adjoint_steps >= ts->adjoint_max_steps) ts->reason = TS_CONVERGED_ITS; 4180 } 4181 PetscFunctionReturn(0); 4182 } 4183 4184 /*@ 4185 TSEvaluateWLTE - Evaluate the weighted local truncation error norm 4186 at the end of a time step with a given order of accuracy. 4187 4188 Collective on TS 4189 4190 Input Arguments: 4191 + ts - time stepping context 4192 . wnormtype - norm type, either NORM_2 or NORM_INFINITY 4193 - order - optional, desired order for the error evaluation or PETSC_DECIDE 4194 4195 Output Arguments: 4196 + order - optional, the actual order of the error evaluation 4197 - wlte - the weighted local truncation error norm 4198 4199 Level: advanced 4200 4201 Notes: 4202 If the timestepper cannot evaluate the error in a particular step 4203 (eg. in the first step or restart steps after event handling), 4204 this routine returns wlte=-1.0 . 4205 4206 .seealso: TSStep(), TSAdapt, TSErrorWeightedNorm() 4207 @*/ 4208 PetscErrorCode TSEvaluateWLTE(TS ts,NormType wnormtype,PetscInt *order,PetscReal *wlte) 4209 { 4210 PetscErrorCode ierr; 4211 4212 PetscFunctionBegin; 4213 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4214 PetscValidType(ts,1); 4215 PetscValidLogicalCollectiveEnum(ts,wnormtype,4); 4216 if (order) PetscValidIntPointer(order,3); 4217 if (order) PetscValidLogicalCollectiveInt(ts,*order,3); 4218 PetscValidRealPointer(wlte,4); 4219 if (wnormtype != NORM_2 && wnormtype != NORM_INFINITY) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"No support for norm type %s",NormTypes[wnormtype]); 4220 if (!ts->ops->evaluatewlte) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"TSEvaluateWLTE not implemented for type '%s'",((PetscObject)ts)->type_name); 4221 ierr = (*ts->ops->evaluatewlte)(ts,wnormtype,order,wlte);CHKERRQ(ierr); 4222 PetscFunctionReturn(0); 4223 } 4224 4225 /*@ 4226 TSEvaluateStep - Evaluate the solution at the end of a time step with a given order of accuracy. 4227 4228 Collective on TS 4229 4230 Input Arguments: 4231 + ts - time stepping context 4232 . order - desired order of accuracy 4233 - done - whether the step was evaluated at this order (pass NULL to generate an error if not available) 4234 4235 Output Arguments: 4236 . U - state at the end of the current step 4237 4238 Level: advanced 4239 4240 Notes: 4241 This function cannot be called until all stages have been evaluated. 4242 It is normally called by adaptive controllers before a step has been accepted and may also be called by the user after TSStep() has returned. 4243 4244 .seealso: TSStep(), TSAdapt 4245 @*/ 4246 PetscErrorCode TSEvaluateStep(TS ts,PetscInt order,Vec U,PetscBool *done) 4247 { 4248 PetscErrorCode ierr; 4249 4250 PetscFunctionBegin; 4251 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4252 PetscValidType(ts,1); 4253 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 4254 if (!ts->ops->evaluatestep) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"TSEvaluateStep not implemented for type '%s'",((PetscObject)ts)->type_name); 4255 ierr = (*ts->ops->evaluatestep)(ts,order,U,done);CHKERRQ(ierr); 4256 PetscFunctionReturn(0); 4257 } 4258 4259 /*@ 4260 TSForwardCostIntegral - Evaluate the cost integral in the forward run. 4261 4262 Collective on TS 4263 4264 Input Arguments: 4265 . ts - time stepping context 4266 4267 Level: advanced 4268 4269 Notes: 4270 This function cannot be called until TSStep() has been completed. 4271 4272 .seealso: TSSolve(), TSAdjointCostIntegral() 4273 @*/ 4274 PetscErrorCode TSForwardCostIntegral(TS ts) 4275 { 4276 PetscErrorCode ierr; 4277 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4278 if (!ts->ops->forwardintegral) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"%s does not provide integral evaluation in the forward run",((PetscObject)ts)->type_name); 4279 ierr = (*ts->ops->forwardintegral)(ts);CHKERRQ(ierr); 4280 PetscFunctionReturn(0); 4281 } 4282 4283 /*@ 4284 TSSolve - Steps the requested number of timesteps. 4285 4286 Collective on TS 4287 4288 Input Parameter: 4289 + ts - the TS context obtained from TSCreate() 4290 - u - the solution vector (can be null if TSSetSolution() was used and TSSetExactFinalTime(ts,TS_EXACTFINALTIME_MATCHSTEP) was not used, 4291 otherwise must contain the initial conditions and will contain the solution at the final requested time 4292 4293 Level: beginner 4294 4295 Notes: 4296 The final time returned by this function may be different from the time of the internally 4297 held state accessible by TSGetSolution() and TSGetTime() because the method may have 4298 stepped over the final time. 4299 4300 .keywords: TS, timestep, solve 4301 4302 .seealso: TSCreate(), TSSetSolution(), TSStep(), TSGetTime(), TSGetSolveTime() 4303 @*/ 4304 PetscErrorCode TSSolve(TS ts,Vec u) 4305 { 4306 Vec solution; 4307 PetscErrorCode ierr; 4308 4309 PetscFunctionBegin; 4310 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4311 if (u) PetscValidHeaderSpecific(u,VEC_CLASSID,2); 4312 4313 if (ts->exact_final_time == TS_EXACTFINALTIME_INTERPOLATE && u) { /* Need ts->vec_sol to be distinct so it is not overwritten when we interpolate at the end */ 4314 if (!ts->vec_sol || u == ts->vec_sol) { 4315 ierr = VecDuplicate(u,&solution);CHKERRQ(ierr); 4316 ierr = TSSetSolution(ts,solution);CHKERRQ(ierr); 4317 ierr = VecDestroy(&solution);CHKERRQ(ierr); /* grant ownership */ 4318 } 4319 ierr = VecCopy(u,ts->vec_sol);CHKERRQ(ierr); 4320 if (ts->forward_solve) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Sensitivity analysis does not support the mode TS_EXACTFINALTIME_INTERPOLATE"); 4321 } else if (u) { 4322 ierr = TSSetSolution(ts,u);CHKERRQ(ierr); 4323 } 4324 ierr = TSSetUp(ts);CHKERRQ(ierr); 4325 ierr = TSTrajectorySetUp(ts->trajectory,ts);CHKERRQ(ierr); 4326 4327 if (ts->max_time >= PETSC_MAX_REAL && ts->max_steps == PETSC_MAX_INT) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONGSTATE,"You must call TSSetMaxTime() or TSSetMaxSteps(), or use -ts_max_time <time> or -ts_max_steps <steps>"); 4328 if (ts->exact_final_time == TS_EXACTFINALTIME_UNSPECIFIED) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONGSTATE,"You must call TSSetExactFinalTime() or use -ts_exact_final_time <stepover,interpolate,matchstep> before calling TSSolve()"); 4329 if (ts->exact_final_time == TS_EXACTFINALTIME_MATCHSTEP && !ts->adapt) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Since TS is not adaptive you cannot use TS_EXACTFINALTIME_MATCHSTEP, suggest TS_EXACTFINALTIME_INTERPOLATE"); 4330 4331 if (ts->forward_solve) { 4332 ierr = TSForwardSetUp(ts);CHKERRQ(ierr); 4333 } 4334 4335 /* reset number of steps only when the step is not restarted. ARKIMEX 4336 restarts the step after an event. Resetting these counters in such case causes 4337 TSTrajectory to incorrectly save the output files 4338 */ 4339 /* reset time step and iteration counters */ 4340 if (!ts->steps) { 4341 ts->ksp_its = 0; 4342 ts->snes_its = 0; 4343 ts->num_snes_failures = 0; 4344 ts->reject = 0; 4345 ts->steprestart = PETSC_TRUE; 4346 ts->steprollback = PETSC_FALSE; 4347 } 4348 if (ts->exact_final_time == TS_EXACTFINALTIME_MATCHSTEP && ts->ptime + ts->time_step > ts->max_time) ts->time_step = ts->max_time - ts->ptime; 4349 ts->reason = TS_CONVERGED_ITERATING; 4350 4351 ierr = TSViewFromOptions(ts,NULL,"-ts_view_pre");CHKERRQ(ierr); 4352 4353 if (ts->ops->solve) { /* This private interface is transitional and should be removed when all implementations are updated. */ 4354 ierr = (*ts->ops->solve)(ts);CHKERRQ(ierr); 4355 if (u) {ierr = VecCopy(ts->vec_sol,u);CHKERRQ(ierr);} 4356 ts->solvetime = ts->ptime; 4357 solution = ts->vec_sol; 4358 } else { /* Step the requested number of timesteps. */ 4359 if (ts->steps >= ts->max_steps) ts->reason = TS_CONVERGED_ITS; 4360 else if (ts->ptime >= ts->max_time) ts->reason = TS_CONVERGED_TIME; 4361 4362 if (!ts->steps) { 4363 ierr = TSTrajectorySet(ts->trajectory,ts,ts->steps,ts->ptime,ts->vec_sol);CHKERRQ(ierr); 4364 ierr = TSEventInitialize(ts->event,ts,ts->ptime,ts->vec_sol);CHKERRQ(ierr); 4365 } 4366 4367 while (!ts->reason) { 4368 ierr = TSMonitor(ts,ts->steps,ts->ptime,ts->vec_sol);CHKERRQ(ierr); 4369 if (!ts->steprollback) { 4370 ierr = TSPreStep(ts);CHKERRQ(ierr); 4371 } 4372 ierr = TSStep(ts);CHKERRQ(ierr); 4373 if (ts->vec_costintegral && ts->costintegralfwd) { /* Must evaluate the cost integral before event is handled. The cost integral value can also be rolled back. */ 4374 ierr = TSForwardCostIntegral(ts);CHKERRQ(ierr); 4375 } 4376 if (ts->forward_solve) { /* compute forward sensitivities before event handling because postevent() may change RHS and jump conditions may have to be applied */ 4377 ierr = TSForwardStep(ts);CHKERRQ(ierr); 4378 } 4379 ierr = TSPostEvaluate(ts);CHKERRQ(ierr); 4380 ierr = TSEventHandler(ts);CHKERRQ(ierr); /* The right-hand side may be changed due to event. Be careful with Any computation using the RHS information after this point. */ 4381 if (ts->steprollback) { 4382 ierr = TSPostEvaluate(ts);CHKERRQ(ierr); 4383 } 4384 if (!ts->steprollback) { 4385 ierr = TSTrajectorySet(ts->trajectory,ts,ts->steps,ts->ptime,ts->vec_sol);CHKERRQ(ierr); 4386 ierr = TSPostStep(ts);CHKERRQ(ierr); 4387 } 4388 } 4389 ierr = TSMonitor(ts,ts->steps,ts->ptime,ts->vec_sol);CHKERRQ(ierr); 4390 4391 if (ts->exact_final_time == TS_EXACTFINALTIME_INTERPOLATE && ts->ptime > ts->max_time) { 4392 ierr = TSInterpolate(ts,ts->max_time,u);CHKERRQ(ierr); 4393 ts->solvetime = ts->max_time; 4394 solution = u; 4395 ierr = TSMonitor(ts,-1,ts->solvetime,solution);CHKERRQ(ierr); 4396 } else { 4397 if (u) {ierr = VecCopy(ts->vec_sol,u);CHKERRQ(ierr);} 4398 ts->solvetime = ts->ptime; 4399 solution = ts->vec_sol; 4400 } 4401 } 4402 4403 ierr = TSViewFromOptions(ts,NULL,"-ts_view");CHKERRQ(ierr); 4404 ierr = VecViewFromOptions(solution,NULL,"-ts_view_solution");CHKERRQ(ierr); 4405 ierr = PetscObjectSAWsBlock((PetscObject)ts);CHKERRQ(ierr); 4406 if (ts->adjoint_solve) { 4407 ierr = TSAdjointSolve(ts);CHKERRQ(ierr); 4408 } 4409 PetscFunctionReturn(0); 4410 } 4411 4412 /*@ 4413 TSAdjointCostIntegral - Evaluate the cost integral in the adjoint run. 4414 4415 Collective on TS 4416 4417 Input Arguments: 4418 . ts - time stepping context 4419 4420 Level: advanced 4421 4422 Notes: 4423 This function cannot be called until TSAdjointStep() has been completed. 4424 4425 .seealso: TSAdjointSolve(), TSAdjointStep 4426 @*/ 4427 PetscErrorCode TSAdjointCostIntegral(TS ts) 4428 { 4429 PetscErrorCode ierr; 4430 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4431 if (!ts->ops->adjointintegral) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"%s does not provide integral evaluation in the adjoint run",((PetscObject)ts)->type_name); 4432 ierr = (*ts->ops->adjointintegral)(ts);CHKERRQ(ierr); 4433 PetscFunctionReturn(0); 4434 } 4435 4436 /*@ 4437 TSAdjointSolve - Solves the discrete ajoint problem for an ODE/DAE 4438 4439 Collective on TS 4440 4441 Input Parameter: 4442 . ts - the TS context obtained from TSCreate() 4443 4444 Options Database: 4445 . -ts_adjoint_view_solution <viewerinfo> - views the first gradient with respect to the initial values 4446 4447 Level: intermediate 4448 4449 Notes: 4450 This must be called after a call to TSSolve() that solves the forward problem 4451 4452 By default this will integrate back to the initial time, one can use TSAdjointSetSteps() to step back to a later time 4453 4454 .keywords: TS, timestep, solve 4455 4456 .seealso: TSCreate(), TSSetCostGradients(), TSSetSolution(), TSAdjointStep() 4457 @*/ 4458 PetscErrorCode TSAdjointSolve(TS ts) 4459 { 4460 PetscErrorCode ierr; 4461 4462 PetscFunctionBegin; 4463 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4464 ierr = TSAdjointSetUp(ts);CHKERRQ(ierr); 4465 4466 /* reset time step and iteration counters */ 4467 ts->adjoint_steps = 0; 4468 ts->ksp_its = 0; 4469 ts->snes_its = 0; 4470 ts->num_snes_failures = 0; 4471 ts->reject = 0; 4472 ts->reason = TS_CONVERGED_ITERATING; 4473 4474 if (!ts->adjoint_max_steps) ts->adjoint_max_steps = ts->steps; 4475 if (ts->adjoint_steps >= ts->adjoint_max_steps) ts->reason = TS_CONVERGED_ITS; 4476 4477 while (!ts->reason) { 4478 ierr = TSTrajectoryGet(ts->trajectory,ts,ts->steps,&ts->ptime);CHKERRQ(ierr); 4479 ierr = TSAdjointMonitor(ts,ts->steps,ts->ptime,ts->vec_sol,ts->numcost,ts->vecs_sensi,ts->vecs_sensip);CHKERRQ(ierr); 4480 ierr = TSAdjointEventHandler(ts);CHKERRQ(ierr); 4481 ierr = TSAdjointStep(ts);CHKERRQ(ierr); 4482 if (ts->vec_costintegral && !ts->costintegralfwd) { 4483 ierr = TSAdjointCostIntegral(ts);CHKERRQ(ierr); 4484 } 4485 } 4486 ierr = TSTrajectoryGet(ts->trajectory,ts,ts->steps,&ts->ptime);CHKERRQ(ierr); 4487 ierr = TSAdjointMonitor(ts,ts->steps,ts->ptime,ts->vec_sol,ts->numcost,ts->vecs_sensi,ts->vecs_sensip);CHKERRQ(ierr); 4488 ts->solvetime = ts->ptime; 4489 ierr = TSTrajectoryViewFromOptions(ts->trajectory,NULL,"-ts_trajectory_view");CHKERRQ(ierr); 4490 ierr = VecViewFromOptions(ts->vecs_sensi[0],(PetscObject) ts, "-ts_adjoint_view_solution");CHKERRQ(ierr); 4491 PetscFunctionReturn(0); 4492 } 4493 4494 /*@C 4495 TSMonitor - Runs all user-provided monitor routines set using TSMonitorSet() 4496 4497 Collective on TS 4498 4499 Input Parameters: 4500 + ts - time stepping context obtained from TSCreate() 4501 . step - step number that has just completed 4502 . ptime - model time of the state 4503 - u - state at the current model time 4504 4505 Notes: 4506 TSMonitor() is typically used automatically within the time stepping implementations. 4507 Users would almost never call this routine directly. 4508 4509 A step of -1 indicates that the monitor is being called on a solution obtained by interpolating from computed solutions 4510 4511 Level: developer 4512 4513 .keywords: TS, timestep 4514 @*/ 4515 PetscErrorCode TSMonitor(TS ts,PetscInt step,PetscReal ptime,Vec u) 4516 { 4517 DM dm; 4518 PetscInt i,n = ts->numbermonitors; 4519 PetscErrorCode ierr; 4520 4521 PetscFunctionBegin; 4522 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4523 PetscValidHeaderSpecific(u,VEC_CLASSID,4); 4524 4525 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 4526 ierr = DMSetOutputSequenceNumber(dm,step,ptime);CHKERRQ(ierr); 4527 4528 ierr = VecLockPush(u);CHKERRQ(ierr); 4529 for (i=0; i<n; i++) { 4530 ierr = (*ts->monitor[i])(ts,step,ptime,u,ts->monitorcontext[i]);CHKERRQ(ierr); 4531 } 4532 ierr = VecLockPop(u);CHKERRQ(ierr); 4533 PetscFunctionReturn(0); 4534 } 4535 4536 /*@C 4537 TSAdjointMonitor - Runs all user-provided adjoint monitor routines set using TSAdjointMonitorSet() 4538 4539 Collective on TS 4540 4541 Input Parameters: 4542 + ts - time stepping context obtained from TSCreate() 4543 . step - step number that has just completed 4544 . ptime - model time of the state 4545 . u - state at the current model time 4546 . numcost - number of cost functions (dimension of lambda or mu) 4547 . lambda - vectors containing the gradients of the cost functions with respect to the ODE/DAE solution variables 4548 - mu - vectors containing the gradients of the cost functions with respect to the problem parameters 4549 4550 Notes: 4551 TSAdjointMonitor() is typically used automatically within the time stepping implementations. 4552 Users would almost never call this routine directly. 4553 4554 Level: developer 4555 4556 .keywords: TS, timestep 4557 @*/ 4558 PetscErrorCode TSAdjointMonitor(TS ts,PetscInt step,PetscReal ptime,Vec u,PetscInt numcost,Vec *lambda, Vec *mu) 4559 { 4560 PetscErrorCode ierr; 4561 PetscInt i,n = ts->numberadjointmonitors; 4562 4563 PetscFunctionBegin; 4564 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4565 PetscValidHeaderSpecific(u,VEC_CLASSID,4); 4566 ierr = VecLockPush(u);CHKERRQ(ierr); 4567 for (i=0; i<n; i++) { 4568 ierr = (*ts->adjointmonitor[i])(ts,step,ptime,u,numcost,lambda,mu,ts->adjointmonitorcontext[i]);CHKERRQ(ierr); 4569 } 4570 ierr = VecLockPop(u);CHKERRQ(ierr); 4571 PetscFunctionReturn(0); 4572 } 4573 4574 /* ------------------------------------------------------------------------*/ 4575 /*@C 4576 TSMonitorLGCtxCreate - Creates a TSMonitorLGCtx context for use with 4577 TS to monitor the solution process graphically in various ways 4578 4579 Collective on TS 4580 4581 Input Parameters: 4582 + host - the X display to open, or null for the local machine 4583 . label - the title to put in the title bar 4584 . x, y - the screen coordinates of the upper left coordinate of the window 4585 . m, n - the screen width and height in pixels 4586 - howoften - if positive then determines the frequency of the plotting, if -1 then only at the final time 4587 4588 Output Parameter: 4589 . ctx - the context 4590 4591 Options Database Key: 4592 + -ts_monitor_lg_timestep - automatically sets line graph monitor 4593 + -ts_monitor_lg_timestep_log - automatically sets line graph monitor 4594 . -ts_monitor_lg_solution - monitor the solution (or certain values of the solution by calling TSMonitorLGSetDisplayVariables() or TSMonitorLGCtxSetDisplayVariables()) 4595 . -ts_monitor_lg_error - monitor the error 4596 . -ts_monitor_lg_ksp_iterations - monitor the number of KSP iterations needed for each timestep 4597 . -ts_monitor_lg_snes_iterations - monitor the number of SNES iterations needed for each timestep 4598 - -lg_use_markers <true,false> - mark the data points (at each time step) on the plot; default is true 4599 4600 Notes: 4601 Use TSMonitorLGCtxDestroy() to destroy. 4602 4603 One can provide a function that transforms the solution before plotting it with TSMonitorLGCtxSetTransform() or TSMonitorLGSetTransform() 4604 4605 Many of the functions that control the monitoring have two forms: TSMonitorLGSet/GetXXXX() and TSMonitorLGCtxSet/GetXXXX() the first take a TS object as the 4606 first argument (if that TS object does not have a TSMonitorLGCtx associated with it the function call is ignored) and the second takes a TSMonitorLGCtx object 4607 as the first argument. 4608 4609 One can control the names displayed for each solution or error variable with TSMonitorLGCtxSetVariableNames() or TSMonitorLGSetVariableNames() 4610 4611 Level: intermediate 4612 4613 .keywords: TS, monitor, line graph, residual 4614 4615 .seealso: TSMonitorLGTimeStep(), TSMonitorSet(), TSMonitorLGSolution(), TSMonitorLGError(), TSMonitorDefault(), VecView(), 4616 TSMonitorLGCtxCreate(), TSMonitorLGCtxSetVariableNames(), TSMonitorLGCtxGetVariableNames(), 4617 TSMonitorLGSetVariableNames(), TSMonitorLGGetVariableNames(), TSMonitorLGSetDisplayVariables(), TSMonitorLGCtxSetDisplayVariables(), 4618 TSMonitorLGCtxSetTransform(), TSMonitorLGSetTransform(), TSMonitorLGError(), TSMonitorLGSNESIterations(), TSMonitorLGKSPIterations(), 4619 TSMonitorEnvelopeCtxCreate(), TSMonitorEnvelopeGetBounds(), TSMonitorEnvelopeCtxDestroy(), TSMonitorEnvelop() 4620 4621 @*/ 4622 PetscErrorCode TSMonitorLGCtxCreate(MPI_Comm comm,const char host[],const char label[],int x,int y,int m,int n,PetscInt howoften,TSMonitorLGCtx *ctx) 4623 { 4624 PetscDraw draw; 4625 PetscErrorCode ierr; 4626 4627 PetscFunctionBegin; 4628 ierr = PetscNew(ctx);CHKERRQ(ierr); 4629 ierr = PetscDrawCreate(comm,host,label,x,y,m,n,&draw);CHKERRQ(ierr); 4630 ierr = PetscDrawSetFromOptions(draw);CHKERRQ(ierr); 4631 ierr = PetscDrawLGCreate(draw,1,&(*ctx)->lg);CHKERRQ(ierr); 4632 ierr = PetscDrawLGSetFromOptions((*ctx)->lg);CHKERRQ(ierr); 4633 ierr = PetscDrawDestroy(&draw);CHKERRQ(ierr); 4634 (*ctx)->howoften = howoften; 4635 PetscFunctionReturn(0); 4636 } 4637 4638 PetscErrorCode TSMonitorLGTimeStep(TS ts,PetscInt step,PetscReal ptime,Vec v,void *monctx) 4639 { 4640 TSMonitorLGCtx ctx = (TSMonitorLGCtx) monctx; 4641 PetscReal x = ptime,y; 4642 PetscErrorCode ierr; 4643 4644 PetscFunctionBegin; 4645 if (step < 0) PetscFunctionReturn(0); /* -1 indicates an interpolated solution */ 4646 if (!step) { 4647 PetscDrawAxis axis; 4648 const char *ylabel = ctx->semilogy ? "Log Time Step" : "Time Step"; 4649 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 4650 ierr = PetscDrawAxisSetLabels(axis,"Timestep as function of time","Time",ylabel);CHKERRQ(ierr); 4651 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 4652 } 4653 ierr = TSGetTimeStep(ts,&y);CHKERRQ(ierr); 4654 if (ctx->semilogy) y = PetscLog10Real(y); 4655 ierr = PetscDrawLGAddPoint(ctx->lg,&x,&y);CHKERRQ(ierr); 4656 if (((ctx->howoften > 0) && (!(step % ctx->howoften))) || ((ctx->howoften == -1) && ts->reason)) { 4657 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 4658 ierr = PetscDrawLGSave(ctx->lg);CHKERRQ(ierr); 4659 } 4660 PetscFunctionReturn(0); 4661 } 4662 4663 /*@C 4664 TSMonitorLGCtxDestroy - Destroys a line graph context that was created 4665 with TSMonitorLGCtxCreate(). 4666 4667 Collective on TSMonitorLGCtx 4668 4669 Input Parameter: 4670 . ctx - the monitor context 4671 4672 Level: intermediate 4673 4674 .keywords: TS, monitor, line graph, destroy 4675 4676 .seealso: TSMonitorLGCtxCreate(), TSMonitorSet(), TSMonitorLGTimeStep(); 4677 @*/ 4678 PetscErrorCode TSMonitorLGCtxDestroy(TSMonitorLGCtx *ctx) 4679 { 4680 PetscErrorCode ierr; 4681 4682 PetscFunctionBegin; 4683 if ((*ctx)->transformdestroy) { 4684 ierr = ((*ctx)->transformdestroy)((*ctx)->transformctx);CHKERRQ(ierr); 4685 } 4686 ierr = PetscDrawLGDestroy(&(*ctx)->lg);CHKERRQ(ierr); 4687 ierr = PetscStrArrayDestroy(&(*ctx)->names);CHKERRQ(ierr); 4688 ierr = PetscStrArrayDestroy(&(*ctx)->displaynames);CHKERRQ(ierr); 4689 ierr = PetscFree((*ctx)->displayvariables);CHKERRQ(ierr); 4690 ierr = PetscFree((*ctx)->displayvalues);CHKERRQ(ierr); 4691 ierr = PetscFree(*ctx);CHKERRQ(ierr); 4692 PetscFunctionReturn(0); 4693 } 4694 4695 /*@ 4696 TSGetTime - Gets the time of the most recently completed step. 4697 4698 Not Collective 4699 4700 Input Parameter: 4701 . ts - the TS context obtained from TSCreate() 4702 4703 Output Parameter: 4704 . t - the current time. This time may not corresponds to the final time set with TSSetMaxTime(), use TSGetSolveTime(). 4705 4706 Level: beginner 4707 4708 Note: 4709 When called during time step evaluation (e.g. during residual evaluation or via hooks set using TSSetPreStep(), 4710 TSSetPreStage(), TSSetPostStage(), or TSSetPostStep()), the time is the time at the start of the step being evaluated. 4711 4712 .seealso: TSGetSolveTime(), TSSetTime(), TSGetTimeStep() 4713 4714 .keywords: TS, get, time 4715 @*/ 4716 PetscErrorCode TSGetTime(TS ts,PetscReal *t) 4717 { 4718 PetscFunctionBegin; 4719 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4720 PetscValidRealPointer(t,2); 4721 *t = ts->ptime; 4722 PetscFunctionReturn(0); 4723 } 4724 4725 /*@ 4726 TSGetPrevTime - Gets the starting time of the previously completed step. 4727 4728 Not Collective 4729 4730 Input Parameter: 4731 . ts - the TS context obtained from TSCreate() 4732 4733 Output Parameter: 4734 . t - the previous time 4735 4736 Level: beginner 4737 4738 .seealso: TSGetTime(), TSGetSolveTime(), TSGetTimeStep() 4739 4740 .keywords: TS, get, time 4741 @*/ 4742 PetscErrorCode TSGetPrevTime(TS ts,PetscReal *t) 4743 { 4744 PetscFunctionBegin; 4745 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4746 PetscValidRealPointer(t,2); 4747 *t = ts->ptime_prev; 4748 PetscFunctionReturn(0); 4749 } 4750 4751 /*@ 4752 TSSetTime - Allows one to reset the time. 4753 4754 Logically Collective on TS 4755 4756 Input Parameters: 4757 + ts - the TS context obtained from TSCreate() 4758 - time - the time 4759 4760 Level: intermediate 4761 4762 .seealso: TSGetTime(), TSSetMaxSteps() 4763 4764 .keywords: TS, set, time 4765 @*/ 4766 PetscErrorCode TSSetTime(TS ts, PetscReal t) 4767 { 4768 PetscFunctionBegin; 4769 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4770 PetscValidLogicalCollectiveReal(ts,t,2); 4771 ts->ptime = t; 4772 PetscFunctionReturn(0); 4773 } 4774 4775 /*@C 4776 TSSetOptionsPrefix - Sets the prefix used for searching for all 4777 TS options in the database. 4778 4779 Logically Collective on TS 4780 4781 Input Parameter: 4782 + ts - The TS context 4783 - prefix - The prefix to prepend to all option names 4784 4785 Notes: 4786 A hyphen (-) must NOT be given at the beginning of the prefix name. 4787 The first character of all runtime options is AUTOMATICALLY the 4788 hyphen. 4789 4790 Level: advanced 4791 4792 .keywords: TS, set, options, prefix, database 4793 4794 .seealso: TSSetFromOptions() 4795 4796 @*/ 4797 PetscErrorCode TSSetOptionsPrefix(TS ts,const char prefix[]) 4798 { 4799 PetscErrorCode ierr; 4800 SNES snes; 4801 4802 PetscFunctionBegin; 4803 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4804 ierr = PetscObjectSetOptionsPrefix((PetscObject)ts,prefix);CHKERRQ(ierr); 4805 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 4806 ierr = SNESSetOptionsPrefix(snes,prefix);CHKERRQ(ierr); 4807 PetscFunctionReturn(0); 4808 } 4809 4810 /*@C 4811 TSAppendOptionsPrefix - Appends to the prefix used for searching for all 4812 TS options in the database. 4813 4814 Logically Collective on TS 4815 4816 Input Parameter: 4817 + ts - The TS context 4818 - prefix - The prefix to prepend to all option names 4819 4820 Notes: 4821 A hyphen (-) must NOT be given at the beginning of the prefix name. 4822 The first character of all runtime options is AUTOMATICALLY the 4823 hyphen. 4824 4825 Level: advanced 4826 4827 .keywords: TS, append, options, prefix, database 4828 4829 .seealso: TSGetOptionsPrefix() 4830 4831 @*/ 4832 PetscErrorCode TSAppendOptionsPrefix(TS ts,const char prefix[]) 4833 { 4834 PetscErrorCode ierr; 4835 SNES snes; 4836 4837 PetscFunctionBegin; 4838 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4839 ierr = PetscObjectAppendOptionsPrefix((PetscObject)ts,prefix);CHKERRQ(ierr); 4840 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 4841 ierr = SNESAppendOptionsPrefix(snes,prefix);CHKERRQ(ierr); 4842 PetscFunctionReturn(0); 4843 } 4844 4845 /*@C 4846 TSGetOptionsPrefix - Sets the prefix used for searching for all 4847 TS options in the database. 4848 4849 Not Collective 4850 4851 Input Parameter: 4852 . ts - The TS context 4853 4854 Output Parameter: 4855 . prefix - A pointer to the prefix string used 4856 4857 Notes: On the fortran side, the user should pass in a string 'prifix' of 4858 sufficient length to hold the prefix. 4859 4860 Level: intermediate 4861 4862 .keywords: TS, get, options, prefix, database 4863 4864 .seealso: TSAppendOptionsPrefix() 4865 @*/ 4866 PetscErrorCode TSGetOptionsPrefix(TS ts,const char *prefix[]) 4867 { 4868 PetscErrorCode ierr; 4869 4870 PetscFunctionBegin; 4871 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4872 PetscValidPointer(prefix,2); 4873 ierr = PetscObjectGetOptionsPrefix((PetscObject)ts,prefix);CHKERRQ(ierr); 4874 PetscFunctionReturn(0); 4875 } 4876 4877 /*@C 4878 TSGetRHSJacobian - Returns the Jacobian J at the present timestep. 4879 4880 Not Collective, but parallel objects are returned if TS is parallel 4881 4882 Input Parameter: 4883 . ts - The TS context obtained from TSCreate() 4884 4885 Output Parameters: 4886 + Amat - The (approximate) Jacobian J of G, where U_t = G(U,t) (or NULL) 4887 . Pmat - The matrix from which the preconditioner is constructed, usually the same as Amat (or NULL) 4888 . func - Function to compute the Jacobian of the RHS (or NULL) 4889 - ctx - User-defined context for Jacobian evaluation routine (or NULL) 4890 4891 Notes: You can pass in NULL for any return argument you do not need. 4892 4893 Level: intermediate 4894 4895 .seealso: TSGetTimeStep(), TSGetMatrices(), TSGetTime(), TSGetStepNumber() 4896 4897 .keywords: TS, timestep, get, matrix, Jacobian 4898 @*/ 4899 PetscErrorCode TSGetRHSJacobian(TS ts,Mat *Amat,Mat *Pmat,TSRHSJacobian *func,void **ctx) 4900 { 4901 PetscErrorCode ierr; 4902 DM dm; 4903 4904 PetscFunctionBegin; 4905 if (Amat || Pmat) { 4906 SNES snes; 4907 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 4908 ierr = SNESSetUpMatrices(snes);CHKERRQ(ierr); 4909 ierr = SNESGetJacobian(snes,Amat,Pmat,NULL,NULL);CHKERRQ(ierr); 4910 } 4911 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 4912 ierr = DMTSGetRHSJacobian(dm,func,ctx);CHKERRQ(ierr); 4913 PetscFunctionReturn(0); 4914 } 4915 4916 /*@C 4917 TSGetIJacobian - Returns the implicit Jacobian at the present timestep. 4918 4919 Not Collective, but parallel objects are returned if TS is parallel 4920 4921 Input Parameter: 4922 . ts - The TS context obtained from TSCreate() 4923 4924 Output Parameters: 4925 + Amat - The (approximate) Jacobian of F(t,U,U_t) 4926 . Pmat - The matrix from which the preconditioner is constructed, often the same as Amat 4927 . f - The function to compute the matrices 4928 - ctx - User-defined context for Jacobian evaluation routine 4929 4930 Notes: You can pass in NULL for any return argument you do not need. 4931 4932 Level: advanced 4933 4934 .seealso: TSGetTimeStep(), TSGetRHSJacobian(), TSGetMatrices(), TSGetTime(), TSGetStepNumber() 4935 4936 .keywords: TS, timestep, get, matrix, Jacobian 4937 @*/ 4938 PetscErrorCode TSGetIJacobian(TS ts,Mat *Amat,Mat *Pmat,TSIJacobian *f,void **ctx) 4939 { 4940 PetscErrorCode ierr; 4941 DM dm; 4942 4943 PetscFunctionBegin; 4944 if (Amat || Pmat) { 4945 SNES snes; 4946 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 4947 ierr = SNESSetUpMatrices(snes);CHKERRQ(ierr); 4948 ierr = SNESGetJacobian(snes,Amat,Pmat,NULL,NULL);CHKERRQ(ierr); 4949 } 4950 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 4951 ierr = DMTSGetIJacobian(dm,f,ctx);CHKERRQ(ierr); 4952 PetscFunctionReturn(0); 4953 } 4954 4955 /*@C 4956 TSMonitorDrawSolution - Monitors progress of the TS solvers by calling 4957 VecView() for the solution at each timestep 4958 4959 Collective on TS 4960 4961 Input Parameters: 4962 + ts - the TS context 4963 . step - current time-step 4964 . ptime - current time 4965 - dummy - either a viewer or NULL 4966 4967 Options Database: 4968 . -ts_monitor_draw_solution_initial - show initial solution as well as current solution 4969 4970 Notes: the initial solution and current solution are not display with a common axis scaling so generally the option -ts_monitor_draw_solution_initial 4971 will look bad 4972 4973 Level: intermediate 4974 4975 .keywords: TS, vector, monitor, view 4976 4977 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 4978 @*/ 4979 PetscErrorCode TSMonitorDrawSolution(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy) 4980 { 4981 PetscErrorCode ierr; 4982 TSMonitorDrawCtx ictx = (TSMonitorDrawCtx)dummy; 4983 PetscDraw draw; 4984 4985 PetscFunctionBegin; 4986 if (!step && ictx->showinitial) { 4987 if (!ictx->initialsolution) { 4988 ierr = VecDuplicate(u,&ictx->initialsolution);CHKERRQ(ierr); 4989 } 4990 ierr = VecCopy(u,ictx->initialsolution);CHKERRQ(ierr); 4991 } 4992 if (!(((ictx->howoften > 0) && (!(step % ictx->howoften))) || ((ictx->howoften == -1) && ts->reason))) PetscFunctionReturn(0); 4993 4994 if (ictx->showinitial) { 4995 PetscReal pause; 4996 ierr = PetscViewerDrawGetPause(ictx->viewer,&pause);CHKERRQ(ierr); 4997 ierr = PetscViewerDrawSetPause(ictx->viewer,0.0);CHKERRQ(ierr); 4998 ierr = VecView(ictx->initialsolution,ictx->viewer);CHKERRQ(ierr); 4999 ierr = PetscViewerDrawSetPause(ictx->viewer,pause);CHKERRQ(ierr); 5000 ierr = PetscViewerDrawSetHold(ictx->viewer,PETSC_TRUE);CHKERRQ(ierr); 5001 } 5002 ierr = VecView(u,ictx->viewer);CHKERRQ(ierr); 5003 if (ictx->showtimestepandtime) { 5004 PetscReal xl,yl,xr,yr,h; 5005 char time[32]; 5006 5007 ierr = PetscViewerDrawGetDraw(ictx->viewer,0,&draw);CHKERRQ(ierr); 5008 ierr = PetscSNPrintf(time,32,"Timestep %d Time %g",(int)step,(double)ptime);CHKERRQ(ierr); 5009 ierr = PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);CHKERRQ(ierr); 5010 h = yl + .95*(yr - yl); 5011 ierr = PetscDrawStringCentered(draw,.5*(xl+xr),h,PETSC_DRAW_BLACK,time);CHKERRQ(ierr); 5012 ierr = PetscDrawFlush(draw);CHKERRQ(ierr); 5013 } 5014 5015 if (ictx->showinitial) { 5016 ierr = PetscViewerDrawSetHold(ictx->viewer,PETSC_FALSE);CHKERRQ(ierr); 5017 } 5018 PetscFunctionReturn(0); 5019 } 5020 5021 /*@C 5022 TSAdjointMonitorDrawSensi - Monitors progress of the adjoint TS solvers by calling 5023 VecView() for the sensitivities to initial states at each timestep 5024 5025 Collective on TS 5026 5027 Input Parameters: 5028 + ts - the TS context 5029 . step - current time-step 5030 . ptime - current time 5031 . u - current state 5032 . numcost - number of cost functions 5033 . lambda - sensitivities to initial conditions 5034 . mu - sensitivities to parameters 5035 - dummy - either a viewer or NULL 5036 5037 Level: intermediate 5038 5039 .keywords: TS, vector, adjoint, monitor, view 5040 5041 .seealso: TSAdjointMonitorSet(), TSAdjointMonitorDefault(), VecView() 5042 @*/ 5043 PetscErrorCode TSAdjointMonitorDrawSensi(TS ts,PetscInt step,PetscReal ptime,Vec u,PetscInt numcost,Vec *lambda,Vec *mu,void *dummy) 5044 { 5045 PetscErrorCode ierr; 5046 TSMonitorDrawCtx ictx = (TSMonitorDrawCtx)dummy; 5047 PetscDraw draw; 5048 PetscReal xl,yl,xr,yr,h; 5049 char time[32]; 5050 5051 PetscFunctionBegin; 5052 if (!(((ictx->howoften > 0) && (!(step % ictx->howoften))) || ((ictx->howoften == -1) && ts->reason))) PetscFunctionReturn(0); 5053 5054 ierr = VecView(lambda[0],ictx->viewer);CHKERRQ(ierr); 5055 ierr = PetscViewerDrawGetDraw(ictx->viewer,0,&draw);CHKERRQ(ierr); 5056 ierr = PetscSNPrintf(time,32,"Timestep %d Time %g",(int)step,(double)ptime);CHKERRQ(ierr); 5057 ierr = PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);CHKERRQ(ierr); 5058 h = yl + .95*(yr - yl); 5059 ierr = PetscDrawStringCentered(draw,.5*(xl+xr),h,PETSC_DRAW_BLACK,time);CHKERRQ(ierr); 5060 ierr = PetscDrawFlush(draw);CHKERRQ(ierr); 5061 PetscFunctionReturn(0); 5062 } 5063 5064 /*@C 5065 TSMonitorDrawSolutionPhase - Monitors progress of the TS solvers by plotting the solution as a phase diagram 5066 5067 Collective on TS 5068 5069 Input Parameters: 5070 + ts - the TS context 5071 . step - current time-step 5072 . ptime - current time 5073 - dummy - either a viewer or NULL 5074 5075 Level: intermediate 5076 5077 .keywords: TS, vector, monitor, view 5078 5079 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 5080 @*/ 5081 PetscErrorCode TSMonitorDrawSolutionPhase(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy) 5082 { 5083 PetscErrorCode ierr; 5084 TSMonitorDrawCtx ictx = (TSMonitorDrawCtx)dummy; 5085 PetscDraw draw; 5086 PetscDrawAxis axis; 5087 PetscInt n; 5088 PetscMPIInt size; 5089 PetscReal U0,U1,xl,yl,xr,yr,h; 5090 char time[32]; 5091 const PetscScalar *U; 5092 5093 PetscFunctionBegin; 5094 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)ts),&size);CHKERRQ(ierr); 5095 if (size != 1) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Only allowed for sequential runs"); 5096 ierr = VecGetSize(u,&n);CHKERRQ(ierr); 5097 if (n != 2) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Only for ODEs with two unknowns"); 5098 5099 ierr = PetscViewerDrawGetDraw(ictx->viewer,0,&draw);CHKERRQ(ierr); 5100 ierr = PetscViewerDrawGetDrawAxis(ictx->viewer,0,&axis);CHKERRQ(ierr); 5101 ierr = PetscDrawAxisGetLimits(axis,&xl,&xr,&yl,&yr);CHKERRQ(ierr); 5102 if (!step) { 5103 ierr = PetscDrawClear(draw);CHKERRQ(ierr); 5104 ierr = PetscDrawAxisDraw(axis);CHKERRQ(ierr); 5105 } 5106 5107 ierr = VecGetArrayRead(u,&U);CHKERRQ(ierr); 5108 U0 = PetscRealPart(U[0]); 5109 U1 = PetscRealPart(U[1]); 5110 ierr = VecRestoreArrayRead(u,&U);CHKERRQ(ierr); 5111 if ((U0 < xl) || (U1 < yl) || (U0 > xr) || (U1 > yr)) PetscFunctionReturn(0); 5112 5113 ierr = PetscDrawCollectiveBegin(draw);CHKERRQ(ierr); 5114 ierr = PetscDrawPoint(draw,U0,U1,PETSC_DRAW_BLACK);CHKERRQ(ierr); 5115 if (ictx->showtimestepandtime) { 5116 ierr = PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);CHKERRQ(ierr); 5117 ierr = PetscSNPrintf(time,32,"Timestep %d Time %g",(int)step,(double)ptime);CHKERRQ(ierr); 5118 h = yl + .95*(yr - yl); 5119 ierr = PetscDrawStringCentered(draw,.5*(xl+xr),h,PETSC_DRAW_BLACK,time);CHKERRQ(ierr); 5120 } 5121 ierr = PetscDrawCollectiveEnd(draw);CHKERRQ(ierr); 5122 ierr = PetscDrawFlush(draw);CHKERRQ(ierr); 5123 ierr = PetscDrawPause(draw);CHKERRQ(ierr); 5124 ierr = PetscDrawSave(draw);CHKERRQ(ierr); 5125 PetscFunctionReturn(0); 5126 } 5127 5128 /*@C 5129 TSMonitorDrawCtxDestroy - Destroys the monitor context for TSMonitorDrawSolution() 5130 5131 Collective on TS 5132 5133 Input Parameters: 5134 . ctx - the monitor context 5135 5136 Level: intermediate 5137 5138 .keywords: TS, vector, monitor, view 5139 5140 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorDrawSolution(), TSMonitorDrawError() 5141 @*/ 5142 PetscErrorCode TSMonitorDrawCtxDestroy(TSMonitorDrawCtx *ictx) 5143 { 5144 PetscErrorCode ierr; 5145 5146 PetscFunctionBegin; 5147 ierr = PetscViewerDestroy(&(*ictx)->viewer);CHKERRQ(ierr); 5148 ierr = VecDestroy(&(*ictx)->initialsolution);CHKERRQ(ierr); 5149 ierr = PetscFree(*ictx);CHKERRQ(ierr); 5150 PetscFunctionReturn(0); 5151 } 5152 5153 /*@C 5154 TSMonitorDrawCtxCreate - Creates the monitor context for TSMonitorDrawCtx 5155 5156 Collective on TS 5157 5158 Input Parameter: 5159 . ts - time-step context 5160 5161 Output Patameter: 5162 . ctx - the monitor context 5163 5164 Options Database: 5165 . -ts_monitor_draw_solution_initial - show initial solution as well as current solution 5166 5167 Level: intermediate 5168 5169 .keywords: TS, vector, monitor, view 5170 5171 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorDrawCtx() 5172 @*/ 5173 PetscErrorCode TSMonitorDrawCtxCreate(MPI_Comm comm,const char host[],const char label[],int x,int y,int m,int n,PetscInt howoften,TSMonitorDrawCtx *ctx) 5174 { 5175 PetscErrorCode ierr; 5176 5177 PetscFunctionBegin; 5178 ierr = PetscNew(ctx);CHKERRQ(ierr); 5179 ierr = PetscViewerDrawOpen(comm,host,label,x,y,m,n,&(*ctx)->viewer);CHKERRQ(ierr); 5180 ierr = PetscViewerSetFromOptions((*ctx)->viewer);CHKERRQ(ierr); 5181 5182 (*ctx)->howoften = howoften; 5183 (*ctx)->showinitial = PETSC_FALSE; 5184 ierr = PetscOptionsGetBool(NULL,NULL,"-ts_monitor_draw_solution_initial",&(*ctx)->showinitial,NULL);CHKERRQ(ierr); 5185 5186 (*ctx)->showtimestepandtime = PETSC_FALSE; 5187 ierr = PetscOptionsGetBool(NULL,NULL,"-ts_monitor_draw_solution_show_time",&(*ctx)->showtimestepandtime,NULL);CHKERRQ(ierr); 5188 PetscFunctionReturn(0); 5189 } 5190 5191 /*@C 5192 TSMonitorDrawError - Monitors progress of the TS solvers by calling 5193 VecView() for the error at each timestep 5194 5195 Collective on TS 5196 5197 Input Parameters: 5198 + ts - the TS context 5199 . step - current time-step 5200 . ptime - current time 5201 - dummy - either a viewer or NULL 5202 5203 Level: intermediate 5204 5205 .keywords: TS, vector, monitor, view 5206 5207 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 5208 @*/ 5209 PetscErrorCode TSMonitorDrawError(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy) 5210 { 5211 PetscErrorCode ierr; 5212 TSMonitorDrawCtx ctx = (TSMonitorDrawCtx)dummy; 5213 PetscViewer viewer = ctx->viewer; 5214 Vec work; 5215 5216 PetscFunctionBegin; 5217 if (!(((ctx->howoften > 0) && (!(step % ctx->howoften))) || ((ctx->howoften == -1) && ts->reason))) PetscFunctionReturn(0); 5218 ierr = VecDuplicate(u,&work);CHKERRQ(ierr); 5219 ierr = TSComputeSolutionFunction(ts,ptime,work);CHKERRQ(ierr); 5220 ierr = VecAXPY(work,-1.0,u);CHKERRQ(ierr); 5221 ierr = VecView(work,viewer);CHKERRQ(ierr); 5222 ierr = VecDestroy(&work);CHKERRQ(ierr); 5223 PetscFunctionReturn(0); 5224 } 5225 5226 #include <petsc/private/dmimpl.h> 5227 /*@ 5228 TSSetDM - Sets the DM that may be used by some nonlinear solvers or preconditioners under the TS 5229 5230 Logically Collective on TS and DM 5231 5232 Input Parameters: 5233 + ts - the ODE integrator object 5234 - dm - the dm, cannot be NULL 5235 5236 Level: intermediate 5237 5238 .seealso: TSGetDM(), SNESSetDM(), SNESGetDM() 5239 @*/ 5240 PetscErrorCode TSSetDM(TS ts,DM dm) 5241 { 5242 PetscErrorCode ierr; 5243 SNES snes; 5244 DMTS tsdm; 5245 5246 PetscFunctionBegin; 5247 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5248 PetscValidHeaderSpecific(dm,DM_CLASSID,2); 5249 ierr = PetscObjectReference((PetscObject)dm);CHKERRQ(ierr); 5250 if (ts->dm) { /* Move the DMTS context over to the new DM unless the new DM already has one */ 5251 if (ts->dm->dmts && !dm->dmts) { 5252 ierr = DMCopyDMTS(ts->dm,dm);CHKERRQ(ierr); 5253 ierr = DMGetDMTS(ts->dm,&tsdm);CHKERRQ(ierr); 5254 if (tsdm->originaldm == ts->dm) { /* Grant write privileges to the replacement DM */ 5255 tsdm->originaldm = dm; 5256 } 5257 } 5258 ierr = DMDestroy(&ts->dm);CHKERRQ(ierr); 5259 } 5260 ts->dm = dm; 5261 5262 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 5263 ierr = SNESSetDM(snes,dm);CHKERRQ(ierr); 5264 PetscFunctionReturn(0); 5265 } 5266 5267 /*@ 5268 TSGetDM - Gets the DM that may be used by some preconditioners 5269 5270 Not Collective 5271 5272 Input Parameter: 5273 . ts - the preconditioner context 5274 5275 Output Parameter: 5276 . dm - the dm 5277 5278 Level: intermediate 5279 5280 .seealso: TSSetDM(), SNESSetDM(), SNESGetDM() 5281 @*/ 5282 PetscErrorCode TSGetDM(TS ts,DM *dm) 5283 { 5284 PetscErrorCode ierr; 5285 5286 PetscFunctionBegin; 5287 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5288 if (!ts->dm) { 5289 ierr = DMShellCreate(PetscObjectComm((PetscObject)ts),&ts->dm);CHKERRQ(ierr); 5290 if (ts->snes) {ierr = SNESSetDM(ts->snes,ts->dm);CHKERRQ(ierr);} 5291 } 5292 *dm = ts->dm; 5293 PetscFunctionReturn(0); 5294 } 5295 5296 /*@ 5297 SNESTSFormFunction - Function to evaluate nonlinear residual 5298 5299 Logically Collective on SNES 5300 5301 Input Parameter: 5302 + snes - nonlinear solver 5303 . U - the current state at which to evaluate the residual 5304 - ctx - user context, must be a TS 5305 5306 Output Parameter: 5307 . F - the nonlinear residual 5308 5309 Notes: 5310 This function is not normally called by users and is automatically registered with the SNES used by TS. 5311 It is most frequently passed to MatFDColoringSetFunction(). 5312 5313 Level: advanced 5314 5315 .seealso: SNESSetFunction(), MatFDColoringSetFunction() 5316 @*/ 5317 PetscErrorCode SNESTSFormFunction(SNES snes,Vec U,Vec F,void *ctx) 5318 { 5319 TS ts = (TS)ctx; 5320 PetscErrorCode ierr; 5321 5322 PetscFunctionBegin; 5323 PetscValidHeaderSpecific(snes,SNES_CLASSID,1); 5324 PetscValidHeaderSpecific(U,VEC_CLASSID,2); 5325 PetscValidHeaderSpecific(F,VEC_CLASSID,3); 5326 PetscValidHeaderSpecific(ts,TS_CLASSID,4); 5327 ierr = (ts->ops->snesfunction)(snes,U,F,ts);CHKERRQ(ierr); 5328 PetscFunctionReturn(0); 5329 } 5330 5331 /*@ 5332 SNESTSFormJacobian - Function to evaluate the Jacobian 5333 5334 Collective on SNES 5335 5336 Input Parameter: 5337 + snes - nonlinear solver 5338 . U - the current state at which to evaluate the residual 5339 - ctx - user context, must be a TS 5340 5341 Output Parameter: 5342 + A - the Jacobian 5343 . B - the preconditioning matrix (may be the same as A) 5344 - flag - indicates any structure change in the matrix 5345 5346 Notes: 5347 This function is not normally called by users and is automatically registered with the SNES used by TS. 5348 5349 Level: developer 5350 5351 .seealso: SNESSetJacobian() 5352 @*/ 5353 PetscErrorCode SNESTSFormJacobian(SNES snes,Vec U,Mat A,Mat B,void *ctx) 5354 { 5355 TS ts = (TS)ctx; 5356 PetscErrorCode ierr; 5357 5358 PetscFunctionBegin; 5359 PetscValidHeaderSpecific(snes,SNES_CLASSID,1); 5360 PetscValidHeaderSpecific(U,VEC_CLASSID,2); 5361 PetscValidPointer(A,3); 5362 PetscValidHeaderSpecific(A,MAT_CLASSID,3); 5363 PetscValidPointer(B,4); 5364 PetscValidHeaderSpecific(B,MAT_CLASSID,4); 5365 PetscValidHeaderSpecific(ts,TS_CLASSID,6); 5366 ierr = (ts->ops->snesjacobian)(snes,U,A,B,ts);CHKERRQ(ierr); 5367 PetscFunctionReturn(0); 5368 } 5369 5370 /*@C 5371 TSComputeRHSFunctionLinear - Evaluate the right hand side via the user-provided Jacobian, for linear problems Udot = A U only 5372 5373 Collective on TS 5374 5375 Input Arguments: 5376 + ts - time stepping context 5377 . t - time at which to evaluate 5378 . U - state at which to evaluate 5379 - ctx - context 5380 5381 Output Arguments: 5382 . F - right hand side 5383 5384 Level: intermediate 5385 5386 Notes: 5387 This function is intended to be passed to TSSetRHSFunction() to evaluate the right hand side for linear problems. 5388 The matrix (and optionally the evaluation context) should be passed to TSSetRHSJacobian(). 5389 5390 .seealso: TSSetRHSFunction(), TSSetRHSJacobian(), TSComputeRHSJacobianConstant() 5391 @*/ 5392 PetscErrorCode TSComputeRHSFunctionLinear(TS ts,PetscReal t,Vec U,Vec F,void *ctx) 5393 { 5394 PetscErrorCode ierr; 5395 Mat Arhs,Brhs; 5396 5397 PetscFunctionBegin; 5398 ierr = TSGetRHSMats_Private(ts,&Arhs,&Brhs);CHKERRQ(ierr); 5399 ierr = TSComputeRHSJacobian(ts,t,U,Arhs,Brhs);CHKERRQ(ierr); 5400 ierr = MatMult(Arhs,U,F);CHKERRQ(ierr); 5401 PetscFunctionReturn(0); 5402 } 5403 5404 /*@C 5405 TSComputeRHSJacobianConstant - Reuses a Jacobian that is time-independent. 5406 5407 Collective on TS 5408 5409 Input Arguments: 5410 + ts - time stepping context 5411 . t - time at which to evaluate 5412 . U - state at which to evaluate 5413 - ctx - context 5414 5415 Output Arguments: 5416 + A - pointer to operator 5417 . B - pointer to preconditioning matrix 5418 - flg - matrix structure flag 5419 5420 Level: intermediate 5421 5422 Notes: 5423 This function is intended to be passed to TSSetRHSJacobian() to evaluate the Jacobian for linear time-independent problems. 5424 5425 .seealso: TSSetRHSFunction(), TSSetRHSJacobian(), TSComputeRHSFunctionLinear() 5426 @*/ 5427 PetscErrorCode TSComputeRHSJacobianConstant(TS ts,PetscReal t,Vec U,Mat A,Mat B,void *ctx) 5428 { 5429 PetscFunctionBegin; 5430 PetscFunctionReturn(0); 5431 } 5432 5433 /*@C 5434 TSComputeIFunctionLinear - Evaluate the left hand side via the user-provided Jacobian, for linear problems only 5435 5436 Collective on TS 5437 5438 Input Arguments: 5439 + ts - time stepping context 5440 . t - time at which to evaluate 5441 . U - state at which to evaluate 5442 . Udot - time derivative of state vector 5443 - ctx - context 5444 5445 Output Arguments: 5446 . F - left hand side 5447 5448 Level: intermediate 5449 5450 Notes: 5451 The assumption here is that the left hand side is of the form A*Udot (and not A*Udot + B*U). For other cases, the 5452 user is required to write their own TSComputeIFunction. 5453 This function is intended to be passed to TSSetIFunction() to evaluate the left hand side for linear problems. 5454 The matrix (and optionally the evaluation context) should be passed to TSSetIJacobian(). 5455 5456 Note that using this function is NOT equivalent to using TSComputeRHSFunctionLinear() since that solves Udot = A U 5457 5458 .seealso: TSSetIFunction(), TSSetIJacobian(), TSComputeIJacobianConstant(), TSComputeRHSFunctionLinear() 5459 @*/ 5460 PetscErrorCode TSComputeIFunctionLinear(TS ts,PetscReal t,Vec U,Vec Udot,Vec F,void *ctx) 5461 { 5462 PetscErrorCode ierr; 5463 Mat A,B; 5464 5465 PetscFunctionBegin; 5466 ierr = TSGetIJacobian(ts,&A,&B,NULL,NULL);CHKERRQ(ierr); 5467 ierr = TSComputeIJacobian(ts,t,U,Udot,1.0,A,B,PETSC_TRUE);CHKERRQ(ierr); 5468 ierr = MatMult(A,Udot,F);CHKERRQ(ierr); 5469 PetscFunctionReturn(0); 5470 } 5471 5472 /*@C 5473 TSComputeIJacobianConstant - Reuses a time-independent for a semi-implicit DAE or ODE 5474 5475 Collective on TS 5476 5477 Input Arguments: 5478 + ts - time stepping context 5479 . t - time at which to evaluate 5480 . U - state at which to evaluate 5481 . Udot - time derivative of state vector 5482 . shift - shift to apply 5483 - ctx - context 5484 5485 Output Arguments: 5486 + A - pointer to operator 5487 . B - pointer to preconditioning matrix 5488 - flg - matrix structure flag 5489 5490 Level: advanced 5491 5492 Notes: 5493 This function is intended to be passed to TSSetIJacobian() to evaluate the Jacobian for linear time-independent problems. 5494 5495 It is only appropriate for problems of the form 5496 5497 $ M Udot = F(U,t) 5498 5499 where M is constant and F is non-stiff. The user must pass M to TSSetIJacobian(). The current implementation only 5500 works with IMEX time integration methods such as TSROSW and TSARKIMEX, since there is no support for de-constructing 5501 an implicit operator of the form 5502 5503 $ shift*M + J 5504 5505 where J is the Jacobian of -F(U). Support may be added in a future version of PETSc, but for now, the user must store 5506 a copy of M or reassemble it when requested. 5507 5508 .seealso: TSSetIFunction(), TSSetIJacobian(), TSComputeIFunctionLinear() 5509 @*/ 5510 PetscErrorCode TSComputeIJacobianConstant(TS ts,PetscReal t,Vec U,Vec Udot,PetscReal shift,Mat A,Mat B,void *ctx) 5511 { 5512 PetscErrorCode ierr; 5513 5514 PetscFunctionBegin; 5515 ierr = MatScale(A, shift / ts->ijacobian.shift);CHKERRQ(ierr); 5516 ts->ijacobian.shift = shift; 5517 PetscFunctionReturn(0); 5518 } 5519 5520 /*@ 5521 TSGetEquationType - Gets the type of the equation that TS is solving. 5522 5523 Not Collective 5524 5525 Input Parameter: 5526 . ts - the TS context 5527 5528 Output Parameter: 5529 . equation_type - see TSEquationType 5530 5531 Level: beginner 5532 5533 .keywords: TS, equation type 5534 5535 .seealso: TSSetEquationType(), TSEquationType 5536 @*/ 5537 PetscErrorCode TSGetEquationType(TS ts,TSEquationType *equation_type) 5538 { 5539 PetscFunctionBegin; 5540 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5541 PetscValidPointer(equation_type,2); 5542 *equation_type = ts->equation_type; 5543 PetscFunctionReturn(0); 5544 } 5545 5546 /*@ 5547 TSSetEquationType - Sets the type of the equation that TS is solving. 5548 5549 Not Collective 5550 5551 Input Parameter: 5552 + ts - the TS context 5553 - equation_type - see TSEquationType 5554 5555 Level: advanced 5556 5557 .keywords: TS, equation type 5558 5559 .seealso: TSGetEquationType(), TSEquationType 5560 @*/ 5561 PetscErrorCode TSSetEquationType(TS ts,TSEquationType equation_type) 5562 { 5563 PetscFunctionBegin; 5564 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5565 ts->equation_type = equation_type; 5566 PetscFunctionReturn(0); 5567 } 5568 5569 /*@ 5570 TSGetConvergedReason - Gets the reason the TS iteration was stopped. 5571 5572 Not Collective 5573 5574 Input Parameter: 5575 . ts - the TS context 5576 5577 Output Parameter: 5578 . reason - negative value indicates diverged, positive value converged, see TSConvergedReason or the 5579 manual pages for the individual convergence tests for complete lists 5580 5581 Level: beginner 5582 5583 Notes: 5584 Can only be called after the call to TSSolve() is complete. 5585 5586 .keywords: TS, nonlinear, set, convergence, test 5587 5588 .seealso: TSSetConvergenceTest(), TSConvergedReason 5589 @*/ 5590 PetscErrorCode TSGetConvergedReason(TS ts,TSConvergedReason *reason) 5591 { 5592 PetscFunctionBegin; 5593 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5594 PetscValidPointer(reason,2); 5595 *reason = ts->reason; 5596 PetscFunctionReturn(0); 5597 } 5598 5599 /*@ 5600 TSSetConvergedReason - Sets the reason for handling the convergence of TSSolve. 5601 5602 Not Collective 5603 5604 Input Parameter: 5605 + ts - the TS context 5606 . reason - negative value indicates diverged, positive value converged, see TSConvergedReason or the 5607 manual pages for the individual convergence tests for complete lists 5608 5609 Level: advanced 5610 5611 Notes: 5612 Can only be called during TSSolve() is active. 5613 5614 .keywords: TS, nonlinear, set, convergence, test 5615 5616 .seealso: TSConvergedReason 5617 @*/ 5618 PetscErrorCode TSSetConvergedReason(TS ts,TSConvergedReason reason) 5619 { 5620 PetscFunctionBegin; 5621 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5622 ts->reason = reason; 5623 PetscFunctionReturn(0); 5624 } 5625 5626 /*@ 5627 TSGetSolveTime - Gets the time after a call to TSSolve() 5628 5629 Not Collective 5630 5631 Input Parameter: 5632 . ts - the TS context 5633 5634 Output Parameter: 5635 . ftime - the final time. This time corresponds to the final time set with TSSetMaxTime() 5636 5637 Level: beginner 5638 5639 Notes: 5640 Can only be called after the call to TSSolve() is complete. 5641 5642 .keywords: TS, nonlinear, set, convergence, test 5643 5644 .seealso: TSSetConvergenceTest(), TSConvergedReason 5645 @*/ 5646 PetscErrorCode TSGetSolveTime(TS ts,PetscReal *ftime) 5647 { 5648 PetscFunctionBegin; 5649 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5650 PetscValidPointer(ftime,2); 5651 *ftime = ts->solvetime; 5652 PetscFunctionReturn(0); 5653 } 5654 5655 /*@ 5656 TSGetSNESIterations - Gets the total number of nonlinear iterations 5657 used by the time integrator. 5658 5659 Not Collective 5660 5661 Input Parameter: 5662 . ts - TS context 5663 5664 Output Parameter: 5665 . nits - number of nonlinear iterations 5666 5667 Notes: 5668 This counter is reset to zero for each successive call to TSSolve(). 5669 5670 Level: intermediate 5671 5672 .keywords: TS, get, number, nonlinear, iterations 5673 5674 .seealso: TSGetKSPIterations() 5675 @*/ 5676 PetscErrorCode TSGetSNESIterations(TS ts,PetscInt *nits) 5677 { 5678 PetscFunctionBegin; 5679 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5680 PetscValidIntPointer(nits,2); 5681 *nits = ts->snes_its; 5682 PetscFunctionReturn(0); 5683 } 5684 5685 /*@ 5686 TSGetKSPIterations - Gets the total number of linear iterations 5687 used by the time integrator. 5688 5689 Not Collective 5690 5691 Input Parameter: 5692 . ts - TS context 5693 5694 Output Parameter: 5695 . lits - number of linear iterations 5696 5697 Notes: 5698 This counter is reset to zero for each successive call to TSSolve(). 5699 5700 Level: intermediate 5701 5702 .keywords: TS, get, number, linear, iterations 5703 5704 .seealso: TSGetSNESIterations(), SNESGetKSPIterations() 5705 @*/ 5706 PetscErrorCode TSGetKSPIterations(TS ts,PetscInt *lits) 5707 { 5708 PetscFunctionBegin; 5709 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5710 PetscValidIntPointer(lits,2); 5711 *lits = ts->ksp_its; 5712 PetscFunctionReturn(0); 5713 } 5714 5715 /*@ 5716 TSGetStepRejections - Gets the total number of rejected steps. 5717 5718 Not Collective 5719 5720 Input Parameter: 5721 . ts - TS context 5722 5723 Output Parameter: 5724 . rejects - number of steps rejected 5725 5726 Notes: 5727 This counter is reset to zero for each successive call to TSSolve(). 5728 5729 Level: intermediate 5730 5731 .keywords: TS, get, number 5732 5733 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetSNESFailures(), TSSetMaxSNESFailures(), TSSetErrorIfStepFails() 5734 @*/ 5735 PetscErrorCode TSGetStepRejections(TS ts,PetscInt *rejects) 5736 { 5737 PetscFunctionBegin; 5738 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5739 PetscValidIntPointer(rejects,2); 5740 *rejects = ts->reject; 5741 PetscFunctionReturn(0); 5742 } 5743 5744 /*@ 5745 TSGetSNESFailures - Gets the total number of failed SNES solves 5746 5747 Not Collective 5748 5749 Input Parameter: 5750 . ts - TS context 5751 5752 Output Parameter: 5753 . fails - number of failed nonlinear solves 5754 5755 Notes: 5756 This counter is reset to zero for each successive call to TSSolve(). 5757 5758 Level: intermediate 5759 5760 .keywords: TS, get, number 5761 5762 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetStepRejections(), TSSetMaxSNESFailures() 5763 @*/ 5764 PetscErrorCode TSGetSNESFailures(TS ts,PetscInt *fails) 5765 { 5766 PetscFunctionBegin; 5767 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5768 PetscValidIntPointer(fails,2); 5769 *fails = ts->num_snes_failures; 5770 PetscFunctionReturn(0); 5771 } 5772 5773 /*@ 5774 TSSetMaxStepRejections - Sets the maximum number of step rejections before a step fails 5775 5776 Not Collective 5777 5778 Input Parameter: 5779 + ts - TS context 5780 - rejects - maximum number of rejected steps, pass -1 for unlimited 5781 5782 Notes: 5783 The counter is reset to zero for each step 5784 5785 Options Database Key: 5786 . -ts_max_reject - Maximum number of step rejections before a step fails 5787 5788 Level: intermediate 5789 5790 .keywords: TS, set, maximum, number 5791 5792 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxSNESFailures(), TSGetStepRejections(), TSGetSNESFailures(), TSSetErrorIfStepFails(), TSGetConvergedReason() 5793 @*/ 5794 PetscErrorCode TSSetMaxStepRejections(TS ts,PetscInt rejects) 5795 { 5796 PetscFunctionBegin; 5797 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5798 ts->max_reject = rejects; 5799 PetscFunctionReturn(0); 5800 } 5801 5802 /*@ 5803 TSSetMaxSNESFailures - Sets the maximum number of failed SNES solves 5804 5805 Not Collective 5806 5807 Input Parameter: 5808 + ts - TS context 5809 - fails - maximum number of failed nonlinear solves, pass -1 for unlimited 5810 5811 Notes: 5812 The counter is reset to zero for each successive call to TSSolve(). 5813 5814 Options Database Key: 5815 . -ts_max_snes_failures - Maximum number of nonlinear solve failures 5816 5817 Level: intermediate 5818 5819 .keywords: TS, set, maximum, number 5820 5821 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetStepRejections(), TSGetSNESFailures(), SNESGetConvergedReason(), TSGetConvergedReason() 5822 @*/ 5823 PetscErrorCode TSSetMaxSNESFailures(TS ts,PetscInt fails) 5824 { 5825 PetscFunctionBegin; 5826 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5827 ts->max_snes_failures = fails; 5828 PetscFunctionReturn(0); 5829 } 5830 5831 /*@ 5832 TSSetErrorIfStepFails - Error if no step succeeds 5833 5834 Not Collective 5835 5836 Input Parameter: 5837 + ts - TS context 5838 - err - PETSC_TRUE to error if no step succeeds, PETSC_FALSE to return without failure 5839 5840 Options Database Key: 5841 . -ts_error_if_step_fails - Error if no step succeeds 5842 5843 Level: intermediate 5844 5845 .keywords: TS, set, error 5846 5847 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetStepRejections(), TSGetSNESFailures(), TSSetErrorIfStepFails(), TSGetConvergedReason() 5848 @*/ 5849 PetscErrorCode TSSetErrorIfStepFails(TS ts,PetscBool err) 5850 { 5851 PetscFunctionBegin; 5852 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5853 ts->errorifstepfailed = err; 5854 PetscFunctionReturn(0); 5855 } 5856 5857 /*@C 5858 TSMonitorSolution - Monitors progress of the TS solvers by VecView() for the solution at each timestep. Normally the viewer is a binary file or a PetscDraw object 5859 5860 Collective on TS 5861 5862 Input Parameters: 5863 + ts - the TS context 5864 . step - current time-step 5865 . ptime - current time 5866 . u - current state 5867 - vf - viewer and its format 5868 5869 Level: intermediate 5870 5871 .keywords: TS, vector, monitor, view 5872 5873 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 5874 @*/ 5875 PetscErrorCode TSMonitorSolution(TS ts,PetscInt step,PetscReal ptime,Vec u,PetscViewerAndFormat *vf) 5876 { 5877 PetscErrorCode ierr; 5878 5879 PetscFunctionBegin; 5880 ierr = PetscViewerPushFormat(vf->viewer,vf->format);CHKERRQ(ierr); 5881 ierr = VecView(u,vf->viewer);CHKERRQ(ierr); 5882 ierr = PetscViewerPopFormat(vf->viewer);CHKERRQ(ierr); 5883 PetscFunctionReturn(0); 5884 } 5885 5886 /*@C 5887 TSMonitorSolutionVTK - Monitors progress of the TS solvers by VecView() for the solution at each timestep. 5888 5889 Collective on TS 5890 5891 Input Parameters: 5892 + ts - the TS context 5893 . step - current time-step 5894 . ptime - current time 5895 . u - current state 5896 - filenametemplate - string containing a format specifier for the integer time step (e.g. %03D) 5897 5898 Level: intermediate 5899 5900 Notes: 5901 The VTK format does not allow writing multiple time steps in the same file, therefore a different file will be written for each time step. 5902 These are named according to the file name template. 5903 5904 This function is normally passed as an argument to TSMonitorSet() along with TSMonitorSolutionVTKDestroy(). 5905 5906 .keywords: TS, vector, monitor, view 5907 5908 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 5909 @*/ 5910 PetscErrorCode TSMonitorSolutionVTK(TS ts,PetscInt step,PetscReal ptime,Vec u,void *filenametemplate) 5911 { 5912 PetscErrorCode ierr; 5913 char filename[PETSC_MAX_PATH_LEN]; 5914 PetscViewer viewer; 5915 5916 PetscFunctionBegin; 5917 if (step < 0) PetscFunctionReturn(0); /* -1 indicates interpolated solution */ 5918 ierr = PetscSNPrintf(filename,sizeof(filename),(const char*)filenametemplate,step);CHKERRQ(ierr); 5919 ierr = PetscViewerVTKOpen(PetscObjectComm((PetscObject)ts),filename,FILE_MODE_WRITE,&viewer);CHKERRQ(ierr); 5920 ierr = VecView(u,viewer);CHKERRQ(ierr); 5921 ierr = PetscViewerDestroy(&viewer);CHKERRQ(ierr); 5922 PetscFunctionReturn(0); 5923 } 5924 5925 /*@C 5926 TSMonitorSolutionVTKDestroy - Destroy context for monitoring 5927 5928 Collective on TS 5929 5930 Input Parameters: 5931 . filenametemplate - string containing a format specifier for the integer time step (e.g. %03D) 5932 5933 Level: intermediate 5934 5935 Note: 5936 This function is normally passed to TSMonitorSet() along with TSMonitorSolutionVTK(). 5937 5938 .keywords: TS, vector, monitor, view 5939 5940 .seealso: TSMonitorSet(), TSMonitorSolutionVTK() 5941 @*/ 5942 PetscErrorCode TSMonitorSolutionVTKDestroy(void *filenametemplate) 5943 { 5944 PetscErrorCode ierr; 5945 5946 PetscFunctionBegin; 5947 ierr = PetscFree(*(char**)filenametemplate);CHKERRQ(ierr); 5948 PetscFunctionReturn(0); 5949 } 5950 5951 /*@ 5952 TSGetAdapt - Get the adaptive controller context for the current method 5953 5954 Collective on TS if controller has not been created yet 5955 5956 Input Arguments: 5957 . ts - time stepping context 5958 5959 Output Arguments: 5960 . adapt - adaptive controller 5961 5962 Level: intermediate 5963 5964 .seealso: TSAdapt, TSAdaptSetType(), TSAdaptChoose() 5965 @*/ 5966 PetscErrorCode TSGetAdapt(TS ts,TSAdapt *adapt) 5967 { 5968 PetscErrorCode ierr; 5969 5970 PetscFunctionBegin; 5971 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5972 PetscValidPointer(adapt,2); 5973 if (!ts->adapt) { 5974 ierr = TSAdaptCreate(PetscObjectComm((PetscObject)ts),&ts->adapt);CHKERRQ(ierr); 5975 ierr = PetscLogObjectParent((PetscObject)ts,(PetscObject)ts->adapt);CHKERRQ(ierr); 5976 ierr = PetscObjectIncrementTabLevel((PetscObject)ts->adapt,(PetscObject)ts,1);CHKERRQ(ierr); 5977 } 5978 *adapt = ts->adapt; 5979 PetscFunctionReturn(0); 5980 } 5981 5982 /*@ 5983 TSSetTolerances - Set tolerances for local truncation error when using adaptive controller 5984 5985 Logically Collective 5986 5987 Input Arguments: 5988 + ts - time integration context 5989 . atol - scalar absolute tolerances, PETSC_DECIDE to leave current value 5990 . vatol - vector of absolute tolerances or NULL, used in preference to atol if present 5991 . rtol - scalar relative tolerances, PETSC_DECIDE to leave current value 5992 - vrtol - vector of relative tolerances or NULL, used in preference to atol if present 5993 5994 Options Database keys: 5995 + -ts_rtol <rtol> - relative tolerance for local truncation error 5996 - -ts_atol <atol> Absolute tolerance for local truncation error 5997 5998 Notes: 5999 With PETSc's implicit schemes for DAE problems, the calculation of the local truncation error 6000 (LTE) includes both the differential and the algebraic variables. If one wants the LTE to be 6001 computed only for the differential or the algebraic part then this can be done using the vector of 6002 tolerances vatol. For example, by setting the tolerance vector with the desired tolerance for the 6003 differential part and infinity for the algebraic part, the LTE calculation will include only the 6004 differential variables. 6005 6006 Level: beginner 6007 6008 .seealso: TS, TSAdapt, TSVecNormWRMS(), TSGetTolerances() 6009 @*/ 6010 PetscErrorCode TSSetTolerances(TS ts,PetscReal atol,Vec vatol,PetscReal rtol,Vec vrtol) 6011 { 6012 PetscErrorCode ierr; 6013 6014 PetscFunctionBegin; 6015 if (atol != PETSC_DECIDE && atol != PETSC_DEFAULT) ts->atol = atol; 6016 if (vatol) { 6017 ierr = PetscObjectReference((PetscObject)vatol);CHKERRQ(ierr); 6018 ierr = VecDestroy(&ts->vatol);CHKERRQ(ierr); 6019 ts->vatol = vatol; 6020 } 6021 if (rtol != PETSC_DECIDE && rtol != PETSC_DEFAULT) ts->rtol = rtol; 6022 if (vrtol) { 6023 ierr = PetscObjectReference((PetscObject)vrtol);CHKERRQ(ierr); 6024 ierr = VecDestroy(&ts->vrtol);CHKERRQ(ierr); 6025 ts->vrtol = vrtol; 6026 } 6027 PetscFunctionReturn(0); 6028 } 6029 6030 /*@ 6031 TSGetTolerances - Get tolerances for local truncation error when using adaptive controller 6032 6033 Logically Collective 6034 6035 Input Arguments: 6036 . ts - time integration context 6037 6038 Output Arguments: 6039 + atol - scalar absolute tolerances, NULL to ignore 6040 . vatol - vector of absolute tolerances, NULL to ignore 6041 . rtol - scalar relative tolerances, NULL to ignore 6042 - vrtol - vector of relative tolerances, NULL to ignore 6043 6044 Level: beginner 6045 6046 .seealso: TS, TSAdapt, TSVecNormWRMS(), TSSetTolerances() 6047 @*/ 6048 PetscErrorCode TSGetTolerances(TS ts,PetscReal *atol,Vec *vatol,PetscReal *rtol,Vec *vrtol) 6049 { 6050 PetscFunctionBegin; 6051 if (atol) *atol = ts->atol; 6052 if (vatol) *vatol = ts->vatol; 6053 if (rtol) *rtol = ts->rtol; 6054 if (vrtol) *vrtol = ts->vrtol; 6055 PetscFunctionReturn(0); 6056 } 6057 6058 /*@ 6059 TSErrorWeightedNorm2 - compute a weighted 2-norm of the difference between two state vectors 6060 6061 Collective on TS 6062 6063 Input Arguments: 6064 + ts - time stepping context 6065 . U - state vector, usually ts->vec_sol 6066 - Y - state vector to be compared to U 6067 6068 Output Arguments: 6069 . norm - weighted norm, a value of 1.0 means that the error matches the tolerances 6070 . norma - weighted norm based on the absolute tolerance, a value of 1.0 means that the error matches the tolerances 6071 . normr - weighted norm based on the relative tolerance, a value of 1.0 means that the error matches the tolerances 6072 6073 Level: developer 6074 6075 .seealso: TSErrorWeightedNorm(), TSErrorWeightedNormInfinity() 6076 @*/ 6077 PetscErrorCode TSErrorWeightedNorm2(TS ts,Vec U,Vec Y,PetscReal *norm,PetscReal *norma,PetscReal *normr) 6078 { 6079 PetscErrorCode ierr; 6080 PetscInt i,n,N,rstart; 6081 PetscInt n_loc,na_loc,nr_loc; 6082 PetscReal n_glb,na_glb,nr_glb; 6083 const PetscScalar *u,*y; 6084 PetscReal sum,suma,sumr,gsum,gsuma,gsumr,diff; 6085 PetscReal tol,tola,tolr; 6086 PetscReal err_loc[6],err_glb[6]; 6087 6088 PetscFunctionBegin; 6089 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 6090 PetscValidHeaderSpecific(U,VEC_CLASSID,2); 6091 PetscValidHeaderSpecific(Y,VEC_CLASSID,3); 6092 PetscValidType(U,2); 6093 PetscValidType(Y,3); 6094 PetscCheckSameComm(U,2,Y,3); 6095 PetscValidPointer(norm,4); 6096 PetscValidPointer(norma,5); 6097 PetscValidPointer(normr,6); 6098 if (U == Y) SETERRQ(PetscObjectComm((PetscObject)U),PETSC_ERR_ARG_IDN,"U and Y cannot be the same vector"); 6099 6100 ierr = VecGetSize(U,&N);CHKERRQ(ierr); 6101 ierr = VecGetLocalSize(U,&n);CHKERRQ(ierr); 6102 ierr = VecGetOwnershipRange(U,&rstart,NULL);CHKERRQ(ierr); 6103 ierr = VecGetArrayRead(U,&u);CHKERRQ(ierr); 6104 ierr = VecGetArrayRead(Y,&y);CHKERRQ(ierr); 6105 sum = 0.; n_loc = 0; 6106 suma = 0.; na_loc = 0; 6107 sumr = 0.; nr_loc = 0; 6108 if (ts->vatol && ts->vrtol) { 6109 const PetscScalar *atol,*rtol; 6110 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6111 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6112 for (i=0; i<n; i++) { 6113 diff = PetscAbsScalar(y[i] - u[i]); 6114 tola = PetscRealPart(atol[i]); 6115 if(tola>0.){ 6116 suma += PetscSqr(diff/tola); 6117 na_loc++; 6118 } 6119 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6120 if(tolr>0.){ 6121 sumr += PetscSqr(diff/tolr); 6122 nr_loc++; 6123 } 6124 tol=tola+tolr; 6125 if(tol>0.){ 6126 sum += PetscSqr(diff/tol); 6127 n_loc++; 6128 } 6129 } 6130 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6131 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6132 } else if (ts->vatol) { /* vector atol, scalar rtol */ 6133 const PetscScalar *atol; 6134 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6135 for (i=0; i<n; i++) { 6136 diff = PetscAbsScalar(y[i] - u[i]); 6137 tola = PetscRealPart(atol[i]); 6138 if(tola>0.){ 6139 suma += PetscSqr(diff/tola); 6140 na_loc++; 6141 } 6142 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6143 if(tolr>0.){ 6144 sumr += PetscSqr(diff/tolr); 6145 nr_loc++; 6146 } 6147 tol=tola+tolr; 6148 if(tol>0.){ 6149 sum += PetscSqr(diff/tol); 6150 n_loc++; 6151 } 6152 } 6153 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6154 } else if (ts->vrtol) { /* scalar atol, vector rtol */ 6155 const PetscScalar *rtol; 6156 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6157 for (i=0; i<n; i++) { 6158 diff = PetscAbsScalar(y[i] - u[i]); 6159 tola = ts->atol; 6160 if(tola>0.){ 6161 suma += PetscSqr(diff/tola); 6162 na_loc++; 6163 } 6164 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6165 if(tolr>0.){ 6166 sumr += PetscSqr(diff/tolr); 6167 nr_loc++; 6168 } 6169 tol=tola+tolr; 6170 if(tol>0.){ 6171 sum += PetscSqr(diff/tol); 6172 n_loc++; 6173 } 6174 } 6175 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6176 } else { /* scalar atol, scalar rtol */ 6177 for (i=0; i<n; i++) { 6178 diff = PetscAbsScalar(y[i] - u[i]); 6179 tola = ts->atol; 6180 if(tola>0.){ 6181 suma += PetscSqr(diff/tola); 6182 na_loc++; 6183 } 6184 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6185 if(tolr>0.){ 6186 sumr += PetscSqr(diff/tolr); 6187 nr_loc++; 6188 } 6189 tol=tola+tolr; 6190 if(tol>0.){ 6191 sum += PetscSqr(diff/tol); 6192 n_loc++; 6193 } 6194 } 6195 } 6196 ierr = VecRestoreArrayRead(U,&u);CHKERRQ(ierr); 6197 ierr = VecRestoreArrayRead(Y,&y);CHKERRQ(ierr); 6198 6199 err_loc[0] = sum; 6200 err_loc[1] = suma; 6201 err_loc[2] = sumr; 6202 err_loc[3] = (PetscReal)n_loc; 6203 err_loc[4] = (PetscReal)na_loc; 6204 err_loc[5] = (PetscReal)nr_loc; 6205 6206 ierr = MPIU_Allreduce(err_loc,err_glb,6,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)ts));CHKERRQ(ierr); 6207 6208 gsum = err_glb[0]; 6209 gsuma = err_glb[1]; 6210 gsumr = err_glb[2]; 6211 n_glb = err_glb[3]; 6212 na_glb = err_glb[4]; 6213 nr_glb = err_glb[5]; 6214 6215 *norm = 0.; 6216 if(n_glb>0. ){*norm = PetscSqrtReal(gsum / n_glb );} 6217 *norma = 0.; 6218 if(na_glb>0.){*norma = PetscSqrtReal(gsuma / na_glb);} 6219 *normr = 0.; 6220 if(nr_glb>0.){*normr = PetscSqrtReal(gsumr / nr_glb);} 6221 6222 if (PetscIsInfOrNanScalar(*norm)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norm"); 6223 if (PetscIsInfOrNanScalar(*norma)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norma"); 6224 if (PetscIsInfOrNanScalar(*normr)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in normr"); 6225 PetscFunctionReturn(0); 6226 } 6227 6228 /*@ 6229 TSErrorWeightedNormInfinity - compute a weighted infinity-norm of the difference between two state vectors 6230 6231 Collective on TS 6232 6233 Input Arguments: 6234 + ts - time stepping context 6235 . U - state vector, usually ts->vec_sol 6236 - Y - state vector to be compared to U 6237 6238 Output Arguments: 6239 . norm - weighted norm, a value of 1.0 means that the error matches the tolerances 6240 . norma - weighted norm based on the absolute tolerance, a value of 1.0 means that the error matches the tolerances 6241 . normr - weighted norm based on the relative tolerance, a value of 1.0 means that the error matches the tolerances 6242 6243 Level: developer 6244 6245 .seealso: TSErrorWeightedNorm(), TSErrorWeightedNorm2() 6246 @*/ 6247 PetscErrorCode TSErrorWeightedNormInfinity(TS ts,Vec U,Vec Y,PetscReal *norm,PetscReal *norma,PetscReal *normr) 6248 { 6249 PetscErrorCode ierr; 6250 PetscInt i,n,N,rstart; 6251 const PetscScalar *u,*y; 6252 PetscReal max,gmax,maxa,gmaxa,maxr,gmaxr; 6253 PetscReal tol,tola,tolr,diff; 6254 PetscReal err_loc[3],err_glb[3]; 6255 6256 PetscFunctionBegin; 6257 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 6258 PetscValidHeaderSpecific(U,VEC_CLASSID,2); 6259 PetscValidHeaderSpecific(Y,VEC_CLASSID,3); 6260 PetscValidType(U,2); 6261 PetscValidType(Y,3); 6262 PetscCheckSameComm(U,2,Y,3); 6263 PetscValidPointer(norm,4); 6264 PetscValidPointer(norma,5); 6265 PetscValidPointer(normr,6); 6266 if (U == Y) SETERRQ(PetscObjectComm((PetscObject)U),PETSC_ERR_ARG_IDN,"U and Y cannot be the same vector"); 6267 6268 ierr = VecGetSize(U,&N);CHKERRQ(ierr); 6269 ierr = VecGetLocalSize(U,&n);CHKERRQ(ierr); 6270 ierr = VecGetOwnershipRange(U,&rstart,NULL);CHKERRQ(ierr); 6271 ierr = VecGetArrayRead(U,&u);CHKERRQ(ierr); 6272 ierr = VecGetArrayRead(Y,&y);CHKERRQ(ierr); 6273 6274 max=0.; 6275 maxa=0.; 6276 maxr=0.; 6277 6278 if (ts->vatol && ts->vrtol) { /* vector atol, vector rtol */ 6279 const PetscScalar *atol,*rtol; 6280 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6281 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6282 6283 for (i=0; i<n; i++) { 6284 diff = PetscAbsScalar(y[i] - u[i]); 6285 tola = PetscRealPart(atol[i]); 6286 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6287 tol = tola+tolr; 6288 if(tola>0.){ 6289 maxa = PetscMax(maxa,diff / tola); 6290 } 6291 if(tolr>0.){ 6292 maxr = PetscMax(maxr,diff / tolr); 6293 } 6294 if(tol>0.){ 6295 max = PetscMax(max,diff / tol); 6296 } 6297 } 6298 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6299 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6300 } else if (ts->vatol) { /* vector atol, scalar rtol */ 6301 const PetscScalar *atol; 6302 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6303 for (i=0; i<n; i++) { 6304 diff = PetscAbsScalar(y[i] - u[i]); 6305 tola = PetscRealPart(atol[i]); 6306 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6307 tol = tola+tolr; 6308 if(tola>0.){ 6309 maxa = PetscMax(maxa,diff / tola); 6310 } 6311 if(tolr>0.){ 6312 maxr = PetscMax(maxr,diff / tolr); 6313 } 6314 if(tol>0.){ 6315 max = PetscMax(max,diff / tol); 6316 } 6317 } 6318 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6319 } else if (ts->vrtol) { /* scalar atol, vector rtol */ 6320 const PetscScalar *rtol; 6321 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6322 6323 for (i=0; i<n; i++) { 6324 diff = PetscAbsScalar(y[i] - u[i]); 6325 tola = ts->atol; 6326 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6327 tol = tola+tolr; 6328 if(tola>0.){ 6329 maxa = PetscMax(maxa,diff / tola); 6330 } 6331 if(tolr>0.){ 6332 maxr = PetscMax(maxr,diff / tolr); 6333 } 6334 if(tol>0.){ 6335 max = PetscMax(max,diff / tol); 6336 } 6337 } 6338 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6339 } else { /* scalar atol, scalar rtol */ 6340 6341 for (i=0; i<n; i++) { 6342 diff = PetscAbsScalar(y[i] - u[i]); 6343 tola = ts->atol; 6344 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6345 tol = tola+tolr; 6346 if(tola>0.){ 6347 maxa = PetscMax(maxa,diff / tola); 6348 } 6349 if(tolr>0.){ 6350 maxr = PetscMax(maxr,diff / tolr); 6351 } 6352 if(tol>0.){ 6353 max = PetscMax(max,diff / tol); 6354 } 6355 } 6356 } 6357 ierr = VecRestoreArrayRead(U,&u);CHKERRQ(ierr); 6358 ierr = VecRestoreArrayRead(Y,&y);CHKERRQ(ierr); 6359 err_loc[0] = max; 6360 err_loc[1] = maxa; 6361 err_loc[2] = maxr; 6362 ierr = MPIU_Allreduce(err_loc,err_glb,3,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)ts));CHKERRQ(ierr); 6363 gmax = err_glb[0]; 6364 gmaxa = err_glb[1]; 6365 gmaxr = err_glb[2]; 6366 6367 *norm = gmax; 6368 *norma = gmaxa; 6369 *normr = gmaxr; 6370 if (PetscIsInfOrNanScalar(*norm)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norm"); 6371 if (PetscIsInfOrNanScalar(*norma)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norma"); 6372 if (PetscIsInfOrNanScalar(*normr)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in normr"); 6373 PetscFunctionReturn(0); 6374 } 6375 6376 /*@ 6377 TSErrorWeightedNorm - compute a weighted norm of the difference between two state vectors based on supplied absolute and relative tolerances 6378 6379 Collective on TS 6380 6381 Input Arguments: 6382 + ts - time stepping context 6383 . U - state vector, usually ts->vec_sol 6384 . Y - state vector to be compared to U 6385 - wnormtype - norm type, either NORM_2 or NORM_INFINITY 6386 6387 Output Arguments: 6388 . norm - weighted norm, a value of 1.0 achieves a balance between absolute and relative tolerances 6389 . norma - weighted norm, a value of 1.0 means that the error meets the absolute tolerance set by the user 6390 . normr - weighted norm, a value of 1.0 means that the error meets the relative tolerance set by the user 6391 6392 Options Database Keys: 6393 . -ts_adapt_wnormtype <wnormtype> - 2, INFINITY 6394 6395 Level: developer 6396 6397 .seealso: TSErrorWeightedNormInfinity(), TSErrorWeightedNorm2(), TSErrorWeightedENorm 6398 @*/ 6399 PetscErrorCode TSErrorWeightedNorm(TS ts,Vec U,Vec Y,NormType wnormtype,PetscReal *norm,PetscReal *norma,PetscReal *normr) 6400 { 6401 PetscErrorCode ierr; 6402 6403 PetscFunctionBegin; 6404 if (wnormtype == NORM_2) { 6405 ierr = TSErrorWeightedNorm2(ts,U,Y,norm,norma,normr);CHKERRQ(ierr); 6406 } else if(wnormtype == NORM_INFINITY) { 6407 ierr = TSErrorWeightedNormInfinity(ts,U,Y,norm,norma,normr);CHKERRQ(ierr); 6408 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for norm type %s",NormTypes[wnormtype]); 6409 PetscFunctionReturn(0); 6410 } 6411 6412 6413 /*@ 6414 TSErrorWeightedENorm2 - compute a weighted 2 error norm based on supplied absolute and relative tolerances 6415 6416 Collective on TS 6417 6418 Input Arguments: 6419 + ts - time stepping context 6420 . E - error vector 6421 . U - state vector, usually ts->vec_sol 6422 - Y - state vector, previous time step 6423 6424 Output Arguments: 6425 . norm - weighted norm, a value of 1.0 means that the error matches the tolerances 6426 . norma - weighted norm based on the absolute tolerance, a value of 1.0 means that the error matches the tolerances 6427 . normr - weighted norm based on the relative tolerance, a value of 1.0 means that the error matches the tolerances 6428 6429 Level: developer 6430 6431 .seealso: TSErrorWeightedENorm(), TSErrorWeightedENormInfinity() 6432 @*/ 6433 PetscErrorCode TSErrorWeightedENorm2(TS ts,Vec E,Vec U,Vec Y,PetscReal *norm,PetscReal *norma,PetscReal *normr) 6434 { 6435 PetscErrorCode ierr; 6436 PetscInt i,n,N,rstart; 6437 PetscInt n_loc,na_loc,nr_loc; 6438 PetscReal n_glb,na_glb,nr_glb; 6439 const PetscScalar *e,*u,*y; 6440 PetscReal err,sum,suma,sumr,gsum,gsuma,gsumr; 6441 PetscReal tol,tola,tolr; 6442 PetscReal err_loc[6],err_glb[6]; 6443 6444 PetscFunctionBegin; 6445 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 6446 PetscValidHeaderSpecific(E,VEC_CLASSID,2); 6447 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 6448 PetscValidHeaderSpecific(Y,VEC_CLASSID,4); 6449 PetscValidType(E,2); 6450 PetscValidType(U,3); 6451 PetscValidType(Y,4); 6452 PetscCheckSameComm(E,2,U,3); 6453 PetscCheckSameComm(U,2,Y,3); 6454 PetscValidPointer(norm,5); 6455 PetscValidPointer(norma,6); 6456 PetscValidPointer(normr,7); 6457 6458 ierr = VecGetSize(E,&N);CHKERRQ(ierr); 6459 ierr = VecGetLocalSize(E,&n);CHKERRQ(ierr); 6460 ierr = VecGetOwnershipRange(E,&rstart,NULL);CHKERRQ(ierr); 6461 ierr = VecGetArrayRead(E,&e);CHKERRQ(ierr); 6462 ierr = VecGetArrayRead(U,&u);CHKERRQ(ierr); 6463 ierr = VecGetArrayRead(Y,&y);CHKERRQ(ierr); 6464 sum = 0.; n_loc = 0; 6465 suma = 0.; na_loc = 0; 6466 sumr = 0.; nr_loc = 0; 6467 if (ts->vatol && ts->vrtol) { 6468 const PetscScalar *atol,*rtol; 6469 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6470 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6471 for (i=0; i<n; i++) { 6472 err = PetscAbsScalar(e[i]); 6473 tola = PetscRealPart(atol[i]); 6474 if(tola>0.){ 6475 suma += PetscSqr(err/tola); 6476 na_loc++; 6477 } 6478 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6479 if(tolr>0.){ 6480 sumr += PetscSqr(err/tolr); 6481 nr_loc++; 6482 } 6483 tol=tola+tolr; 6484 if(tol>0.){ 6485 sum += PetscSqr(err/tol); 6486 n_loc++; 6487 } 6488 } 6489 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6490 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6491 } else if (ts->vatol) { /* vector atol, scalar rtol */ 6492 const PetscScalar *atol; 6493 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6494 for (i=0; i<n; i++) { 6495 err = PetscAbsScalar(e[i]); 6496 tola = PetscRealPart(atol[i]); 6497 if(tola>0.){ 6498 suma += PetscSqr(err/tola); 6499 na_loc++; 6500 } 6501 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6502 if(tolr>0.){ 6503 sumr += PetscSqr(err/tolr); 6504 nr_loc++; 6505 } 6506 tol=tola+tolr; 6507 if(tol>0.){ 6508 sum += PetscSqr(err/tol); 6509 n_loc++; 6510 } 6511 } 6512 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6513 } else if (ts->vrtol) { /* scalar atol, vector rtol */ 6514 const PetscScalar *rtol; 6515 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6516 for (i=0; i<n; i++) { 6517 err = PetscAbsScalar(e[i]); 6518 tola = ts->atol; 6519 if(tola>0.){ 6520 suma += PetscSqr(err/tola); 6521 na_loc++; 6522 } 6523 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6524 if(tolr>0.){ 6525 sumr += PetscSqr(err/tolr); 6526 nr_loc++; 6527 } 6528 tol=tola+tolr; 6529 if(tol>0.){ 6530 sum += PetscSqr(err/tol); 6531 n_loc++; 6532 } 6533 } 6534 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6535 } else { /* scalar atol, scalar rtol */ 6536 for (i=0; i<n; i++) { 6537 err = PetscAbsScalar(e[i]); 6538 tola = ts->atol; 6539 if(tola>0.){ 6540 suma += PetscSqr(err/tola); 6541 na_loc++; 6542 } 6543 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6544 if(tolr>0.){ 6545 sumr += PetscSqr(err/tolr); 6546 nr_loc++; 6547 } 6548 tol=tola+tolr; 6549 if(tol>0.){ 6550 sum += PetscSqr(err/tol); 6551 n_loc++; 6552 } 6553 } 6554 } 6555 ierr = VecRestoreArrayRead(E,&e);CHKERRQ(ierr); 6556 ierr = VecRestoreArrayRead(U,&u);CHKERRQ(ierr); 6557 ierr = VecRestoreArrayRead(Y,&y);CHKERRQ(ierr); 6558 6559 err_loc[0] = sum; 6560 err_loc[1] = suma; 6561 err_loc[2] = sumr; 6562 err_loc[3] = (PetscReal)n_loc; 6563 err_loc[4] = (PetscReal)na_loc; 6564 err_loc[5] = (PetscReal)nr_loc; 6565 6566 ierr = MPIU_Allreduce(err_loc,err_glb,6,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)ts));CHKERRQ(ierr); 6567 6568 gsum = err_glb[0]; 6569 gsuma = err_glb[1]; 6570 gsumr = err_glb[2]; 6571 n_glb = err_glb[3]; 6572 na_glb = err_glb[4]; 6573 nr_glb = err_glb[5]; 6574 6575 *norm = 0.; 6576 if(n_glb>0. ){*norm = PetscSqrtReal(gsum / n_glb );} 6577 *norma = 0.; 6578 if(na_glb>0.){*norma = PetscSqrtReal(gsuma / na_glb);} 6579 *normr = 0.; 6580 if(nr_glb>0.){*normr = PetscSqrtReal(gsumr / nr_glb);} 6581 6582 if (PetscIsInfOrNanScalar(*norm)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norm"); 6583 if (PetscIsInfOrNanScalar(*norma)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norma"); 6584 if (PetscIsInfOrNanScalar(*normr)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in normr"); 6585 PetscFunctionReturn(0); 6586 } 6587 6588 /*@ 6589 TSErrorWeightedENormInfinity - compute a weighted infinity error norm based on supplied absolute and relative tolerances 6590 Collective on TS 6591 6592 Input Arguments: 6593 + ts - time stepping context 6594 . E - error vector 6595 . U - state vector, usually ts->vec_sol 6596 - Y - state vector, previous time step 6597 6598 Output Arguments: 6599 . norm - weighted norm, a value of 1.0 means that the error matches the tolerances 6600 . norma - weighted norm based on the absolute tolerance, a value of 1.0 means that the error matches the tolerances 6601 . normr - weighted norm based on the relative tolerance, a value of 1.0 means that the error matches the tolerances 6602 6603 Level: developer 6604 6605 .seealso: TSErrorWeightedENorm(), TSErrorWeightedENorm2() 6606 @*/ 6607 PetscErrorCode TSErrorWeightedENormInfinity(TS ts,Vec E,Vec U,Vec Y,PetscReal *norm,PetscReal *norma,PetscReal *normr) 6608 { 6609 PetscErrorCode ierr; 6610 PetscInt i,n,N,rstart; 6611 const PetscScalar *e,*u,*y; 6612 PetscReal err,max,gmax,maxa,gmaxa,maxr,gmaxr; 6613 PetscReal tol,tola,tolr; 6614 PetscReal err_loc[3],err_glb[3]; 6615 6616 PetscFunctionBegin; 6617 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 6618 PetscValidHeaderSpecific(E,VEC_CLASSID,2); 6619 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 6620 PetscValidHeaderSpecific(Y,VEC_CLASSID,4); 6621 PetscValidType(E,2); 6622 PetscValidType(U,3); 6623 PetscValidType(Y,4); 6624 PetscCheckSameComm(E,2,U,3); 6625 PetscCheckSameComm(U,2,Y,3); 6626 PetscValidPointer(norm,5); 6627 PetscValidPointer(norma,6); 6628 PetscValidPointer(normr,7); 6629 6630 ierr = VecGetSize(E,&N);CHKERRQ(ierr); 6631 ierr = VecGetLocalSize(E,&n);CHKERRQ(ierr); 6632 ierr = VecGetOwnershipRange(E,&rstart,NULL);CHKERRQ(ierr); 6633 ierr = VecGetArrayRead(E,&e);CHKERRQ(ierr); 6634 ierr = VecGetArrayRead(U,&u);CHKERRQ(ierr); 6635 ierr = VecGetArrayRead(Y,&y);CHKERRQ(ierr); 6636 6637 max=0.; 6638 maxa=0.; 6639 maxr=0.; 6640 6641 if (ts->vatol && ts->vrtol) { /* vector atol, vector rtol */ 6642 const PetscScalar *atol,*rtol; 6643 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6644 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6645 6646 for (i=0; i<n; i++) { 6647 err = PetscAbsScalar(e[i]); 6648 tola = PetscRealPart(atol[i]); 6649 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6650 tol = tola+tolr; 6651 if(tola>0.){ 6652 maxa = PetscMax(maxa,err / tola); 6653 } 6654 if(tolr>0.){ 6655 maxr = PetscMax(maxr,err / tolr); 6656 } 6657 if(tol>0.){ 6658 max = PetscMax(max,err / tol); 6659 } 6660 } 6661 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6662 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6663 } else if (ts->vatol) { /* vector atol, scalar rtol */ 6664 const PetscScalar *atol; 6665 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6666 for (i=0; i<n; i++) { 6667 err = PetscAbsScalar(e[i]); 6668 tola = PetscRealPart(atol[i]); 6669 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6670 tol = tola+tolr; 6671 if(tola>0.){ 6672 maxa = PetscMax(maxa,err / tola); 6673 } 6674 if(tolr>0.){ 6675 maxr = PetscMax(maxr,err / tolr); 6676 } 6677 if(tol>0.){ 6678 max = PetscMax(max,err / tol); 6679 } 6680 } 6681 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6682 } else if (ts->vrtol) { /* scalar atol, vector rtol */ 6683 const PetscScalar *rtol; 6684 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6685 6686 for (i=0; i<n; i++) { 6687 err = PetscAbsScalar(e[i]); 6688 tola = ts->atol; 6689 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6690 tol = tola+tolr; 6691 if(tola>0.){ 6692 maxa = PetscMax(maxa,err / tola); 6693 } 6694 if(tolr>0.){ 6695 maxr = PetscMax(maxr,err / tolr); 6696 } 6697 if(tol>0.){ 6698 max = PetscMax(max,err / tol); 6699 } 6700 } 6701 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6702 } else { /* scalar atol, scalar rtol */ 6703 6704 for (i=0; i<n; i++) { 6705 err = PetscAbsScalar(e[i]); 6706 tola = ts->atol; 6707 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6708 tol = tola+tolr; 6709 if(tola>0.){ 6710 maxa = PetscMax(maxa,err / tola); 6711 } 6712 if(tolr>0.){ 6713 maxr = PetscMax(maxr,err / tolr); 6714 } 6715 if(tol>0.){ 6716 max = PetscMax(max,err / tol); 6717 } 6718 } 6719 } 6720 ierr = VecRestoreArrayRead(E,&e);CHKERRQ(ierr); 6721 ierr = VecRestoreArrayRead(U,&u);CHKERRQ(ierr); 6722 ierr = VecRestoreArrayRead(Y,&y);CHKERRQ(ierr); 6723 err_loc[0] = max; 6724 err_loc[1] = maxa; 6725 err_loc[2] = maxr; 6726 ierr = MPIU_Allreduce(err_loc,err_glb,3,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)ts));CHKERRQ(ierr); 6727 gmax = err_glb[0]; 6728 gmaxa = err_glb[1]; 6729 gmaxr = err_glb[2]; 6730 6731 *norm = gmax; 6732 *norma = gmaxa; 6733 *normr = gmaxr; 6734 if (PetscIsInfOrNanScalar(*norm)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norm"); 6735 if (PetscIsInfOrNanScalar(*norma)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norma"); 6736 if (PetscIsInfOrNanScalar(*normr)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in normr"); 6737 PetscFunctionReturn(0); 6738 } 6739 6740 /*@ 6741 TSErrorWeightedENorm - compute a weighted error norm based on supplied absolute and relative tolerances 6742 6743 Collective on TS 6744 6745 Input Arguments: 6746 + ts - time stepping context 6747 . E - error vector 6748 . U - state vector, usually ts->vec_sol 6749 . Y - state vector, previous time step 6750 - wnormtype - norm type, either NORM_2 or NORM_INFINITY 6751 6752 Output Arguments: 6753 . norm - weighted norm, a value of 1.0 achieves a balance between absolute and relative tolerances 6754 . norma - weighted norm, a value of 1.0 means that the error meets the absolute tolerance set by the user 6755 . normr - weighted norm, a value of 1.0 means that the error meets the relative tolerance set by the user 6756 6757 Options Database Keys: 6758 . -ts_adapt_wnormtype <wnormtype> - 2, INFINITY 6759 6760 Level: developer 6761 6762 .seealso: TSErrorWeightedENormInfinity(), TSErrorWeightedENorm2(), TSErrorWeightedNormInfinity(), TSErrorWeightedNorm2() 6763 @*/ 6764 PetscErrorCode TSErrorWeightedENorm(TS ts,Vec E,Vec U,Vec Y,NormType wnormtype,PetscReal *norm,PetscReal *norma,PetscReal *normr) 6765 { 6766 PetscErrorCode ierr; 6767 6768 PetscFunctionBegin; 6769 if (wnormtype == NORM_2) { 6770 ierr = TSErrorWeightedENorm2(ts,E,U,Y,norm,norma,normr);CHKERRQ(ierr); 6771 } else if(wnormtype == NORM_INFINITY) { 6772 ierr = TSErrorWeightedENormInfinity(ts,E,U,Y,norm,norma,normr);CHKERRQ(ierr); 6773 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for norm type %s",NormTypes[wnormtype]); 6774 PetscFunctionReturn(0); 6775 } 6776 6777 6778 /*@ 6779 TSSetCFLTimeLocal - Set the local CFL constraint relative to forward Euler 6780 6781 Logically Collective on TS 6782 6783 Input Arguments: 6784 + ts - time stepping context 6785 - cfltime - maximum stable time step if using forward Euler (value can be different on each process) 6786 6787 Note: 6788 After calling this function, the global CFL time can be obtained by calling TSGetCFLTime() 6789 6790 Level: intermediate 6791 6792 .seealso: TSGetCFLTime(), TSADAPTCFL 6793 @*/ 6794 PetscErrorCode TSSetCFLTimeLocal(TS ts,PetscReal cfltime) 6795 { 6796 PetscFunctionBegin; 6797 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 6798 ts->cfltime_local = cfltime; 6799 ts->cfltime = -1.; 6800 PetscFunctionReturn(0); 6801 } 6802 6803 /*@ 6804 TSGetCFLTime - Get the maximum stable time step according to CFL criteria applied to forward Euler 6805 6806 Collective on TS 6807 6808 Input Arguments: 6809 . ts - time stepping context 6810 6811 Output Arguments: 6812 . cfltime - maximum stable time step for forward Euler 6813 6814 Level: advanced 6815 6816 .seealso: TSSetCFLTimeLocal() 6817 @*/ 6818 PetscErrorCode TSGetCFLTime(TS ts,PetscReal *cfltime) 6819 { 6820 PetscErrorCode ierr; 6821 6822 PetscFunctionBegin; 6823 if (ts->cfltime < 0) { 6824 ierr = MPIU_Allreduce(&ts->cfltime_local,&ts->cfltime,1,MPIU_REAL,MPIU_MIN,PetscObjectComm((PetscObject)ts));CHKERRQ(ierr); 6825 } 6826 *cfltime = ts->cfltime; 6827 PetscFunctionReturn(0); 6828 } 6829 6830 /*@ 6831 TSVISetVariableBounds - Sets the lower and upper bounds for the solution vector. xl <= x <= xu 6832 6833 Input Parameters: 6834 . ts - the TS context. 6835 . xl - lower bound. 6836 . xu - upper bound. 6837 6838 Notes: 6839 If this routine is not called then the lower and upper bounds are set to 6840 PETSC_NINFINITY and PETSC_INFINITY respectively during SNESSetUp(). 6841 6842 Level: advanced 6843 6844 @*/ 6845 PetscErrorCode TSVISetVariableBounds(TS ts, Vec xl, Vec xu) 6846 { 6847 PetscErrorCode ierr; 6848 SNES snes; 6849 6850 PetscFunctionBegin; 6851 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 6852 ierr = SNESVISetVariableBounds(snes,xl,xu);CHKERRQ(ierr); 6853 PetscFunctionReturn(0); 6854 } 6855 6856 #if defined(PETSC_HAVE_MATLAB_ENGINE) 6857 #include <mex.h> 6858 6859 typedef struct {char *funcname; mxArray *ctx;} TSMatlabContext; 6860 6861 /* 6862 TSComputeFunction_Matlab - Calls the function that has been set with 6863 TSSetFunctionMatlab(). 6864 6865 Collective on TS 6866 6867 Input Parameters: 6868 + snes - the TS context 6869 - u - input vector 6870 6871 Output Parameter: 6872 . y - function vector, as set by TSSetFunction() 6873 6874 Notes: 6875 TSComputeFunction() is typically used within nonlinear solvers 6876 implementations, so most users would not generally call this routine 6877 themselves. 6878 6879 Level: developer 6880 6881 .keywords: TS, nonlinear, compute, function 6882 6883 .seealso: TSSetFunction(), TSGetFunction() 6884 */ 6885 PetscErrorCode TSComputeFunction_Matlab(TS snes,PetscReal time,Vec u,Vec udot,Vec y, void *ctx) 6886 { 6887 PetscErrorCode ierr; 6888 TSMatlabContext *sctx = (TSMatlabContext*)ctx; 6889 int nlhs = 1,nrhs = 7; 6890 mxArray *plhs[1],*prhs[7]; 6891 long long int lx = 0,lxdot = 0,ly = 0,ls = 0; 6892 6893 PetscFunctionBegin; 6894 PetscValidHeaderSpecific(snes,TS_CLASSID,1); 6895 PetscValidHeaderSpecific(u,VEC_CLASSID,3); 6896 PetscValidHeaderSpecific(udot,VEC_CLASSID,4); 6897 PetscValidHeaderSpecific(y,VEC_CLASSID,5); 6898 PetscCheckSameComm(snes,1,u,3); 6899 PetscCheckSameComm(snes,1,y,5); 6900 6901 ierr = PetscMemcpy(&ls,&snes,sizeof(snes));CHKERRQ(ierr); 6902 ierr = PetscMemcpy(&lx,&u,sizeof(u));CHKERRQ(ierr); 6903 ierr = PetscMemcpy(&lxdot,&udot,sizeof(udot));CHKERRQ(ierr); 6904 ierr = PetscMemcpy(&ly,&y,sizeof(u));CHKERRQ(ierr); 6905 6906 prhs[0] = mxCreateDoubleScalar((double)ls); 6907 prhs[1] = mxCreateDoubleScalar(time); 6908 prhs[2] = mxCreateDoubleScalar((double)lx); 6909 prhs[3] = mxCreateDoubleScalar((double)lxdot); 6910 prhs[4] = mxCreateDoubleScalar((double)ly); 6911 prhs[5] = mxCreateString(sctx->funcname); 6912 prhs[6] = sctx->ctx; 6913 ierr = mexCallMATLAB(nlhs,plhs,nrhs,prhs,"PetscTSComputeFunctionInternal");CHKERRQ(ierr); 6914 ierr = mxGetScalar(plhs[0]);CHKERRQ(ierr); 6915 mxDestroyArray(prhs[0]); 6916 mxDestroyArray(prhs[1]); 6917 mxDestroyArray(prhs[2]); 6918 mxDestroyArray(prhs[3]); 6919 mxDestroyArray(prhs[4]); 6920 mxDestroyArray(prhs[5]); 6921 mxDestroyArray(plhs[0]); 6922 PetscFunctionReturn(0); 6923 } 6924 6925 /* 6926 TSSetFunctionMatlab - Sets the function evaluation routine and function 6927 vector for use by the TS routines in solving ODEs 6928 equations from MATLAB. Here the function is a string containing the name of a MATLAB function 6929 6930 Logically Collective on TS 6931 6932 Input Parameters: 6933 + ts - the TS context 6934 - func - function evaluation routine 6935 6936 Calling sequence of func: 6937 $ func (TS ts,PetscReal time,Vec u,Vec udot,Vec f,void *ctx); 6938 6939 Level: beginner 6940 6941 .keywords: TS, nonlinear, set, function 6942 6943 .seealso: TSGetFunction(), TSComputeFunction(), TSSetJacobian(), TSSetFunction() 6944 */ 6945 PetscErrorCode TSSetFunctionMatlab(TS ts,const char *func,mxArray *ctx) 6946 { 6947 PetscErrorCode ierr; 6948 TSMatlabContext *sctx; 6949 6950 PetscFunctionBegin; 6951 /* currently sctx is memory bleed */ 6952 ierr = PetscNew(&sctx);CHKERRQ(ierr); 6953 ierr = PetscStrallocpy(func,&sctx->funcname);CHKERRQ(ierr); 6954 /* 6955 This should work, but it doesn't 6956 sctx->ctx = ctx; 6957 mexMakeArrayPersistent(sctx->ctx); 6958 */ 6959 sctx->ctx = mxDuplicateArray(ctx); 6960 6961 ierr = TSSetIFunction(ts,NULL,TSComputeFunction_Matlab,sctx);CHKERRQ(ierr); 6962 PetscFunctionReturn(0); 6963 } 6964 6965 /* 6966 TSComputeJacobian_Matlab - Calls the function that has been set with 6967 TSSetJacobianMatlab(). 6968 6969 Collective on TS 6970 6971 Input Parameters: 6972 + ts - the TS context 6973 . u - input vector 6974 . A, B - the matrices 6975 - ctx - user context 6976 6977 Level: developer 6978 6979 .keywords: TS, nonlinear, compute, function 6980 6981 .seealso: TSSetFunction(), TSGetFunction() 6982 @*/ 6983 PetscErrorCode TSComputeJacobian_Matlab(TS ts,PetscReal time,Vec u,Vec udot,PetscReal shift,Mat A,Mat B,void *ctx) 6984 { 6985 PetscErrorCode ierr; 6986 TSMatlabContext *sctx = (TSMatlabContext*)ctx; 6987 int nlhs = 2,nrhs = 9; 6988 mxArray *plhs[2],*prhs[9]; 6989 long long int lx = 0,lxdot = 0,lA = 0,ls = 0, lB = 0; 6990 6991 PetscFunctionBegin; 6992 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 6993 PetscValidHeaderSpecific(u,VEC_CLASSID,3); 6994 6995 /* call Matlab function in ctx with arguments u and y */ 6996 6997 ierr = PetscMemcpy(&ls,&ts,sizeof(ts));CHKERRQ(ierr); 6998 ierr = PetscMemcpy(&lx,&u,sizeof(u));CHKERRQ(ierr); 6999 ierr = PetscMemcpy(&lxdot,&udot,sizeof(u));CHKERRQ(ierr); 7000 ierr = PetscMemcpy(&lA,A,sizeof(u));CHKERRQ(ierr); 7001 ierr = PetscMemcpy(&lB,B,sizeof(u));CHKERRQ(ierr); 7002 7003 prhs[0] = mxCreateDoubleScalar((double)ls); 7004 prhs[1] = mxCreateDoubleScalar((double)time); 7005 prhs[2] = mxCreateDoubleScalar((double)lx); 7006 prhs[3] = mxCreateDoubleScalar((double)lxdot); 7007 prhs[4] = mxCreateDoubleScalar((double)shift); 7008 prhs[5] = mxCreateDoubleScalar((double)lA); 7009 prhs[6] = mxCreateDoubleScalar((double)lB); 7010 prhs[7] = mxCreateString(sctx->funcname); 7011 prhs[8] = sctx->ctx; 7012 ierr = mexCallMATLAB(nlhs,plhs,nrhs,prhs,"PetscTSComputeJacobianInternal");CHKERRQ(ierr); 7013 ierr = mxGetScalar(plhs[0]);CHKERRQ(ierr); 7014 mxDestroyArray(prhs[0]); 7015 mxDestroyArray(prhs[1]); 7016 mxDestroyArray(prhs[2]); 7017 mxDestroyArray(prhs[3]); 7018 mxDestroyArray(prhs[4]); 7019 mxDestroyArray(prhs[5]); 7020 mxDestroyArray(prhs[6]); 7021 mxDestroyArray(prhs[7]); 7022 mxDestroyArray(plhs[0]); 7023 mxDestroyArray(plhs[1]); 7024 PetscFunctionReturn(0); 7025 } 7026 7027 /* 7028 TSSetJacobianMatlab - Sets the Jacobian function evaluation routine and two empty Jacobian matrices 7029 vector for use by the TS routines in solving ODEs from MATLAB. Here the function is a string containing the name of a MATLAB function 7030 7031 Logically Collective on TS 7032 7033 Input Parameters: 7034 + ts - the TS context 7035 . A,B - Jacobian matrices 7036 . func - function evaluation routine 7037 - ctx - user context 7038 7039 Calling sequence of func: 7040 $ flag = func (TS ts,PetscReal time,Vec u,Vec udot,Mat A,Mat B,void *ctx); 7041 7042 Level: developer 7043 7044 .keywords: TS, nonlinear, set, function 7045 7046 .seealso: TSGetFunction(), TSComputeFunction(), TSSetJacobian(), TSSetFunction() 7047 */ 7048 PetscErrorCode TSSetJacobianMatlab(TS ts,Mat A,Mat B,const char *func,mxArray *ctx) 7049 { 7050 PetscErrorCode ierr; 7051 TSMatlabContext *sctx; 7052 7053 PetscFunctionBegin; 7054 /* currently sctx is memory bleed */ 7055 ierr = PetscNew(&sctx);CHKERRQ(ierr); 7056 ierr = PetscStrallocpy(func,&sctx->funcname);CHKERRQ(ierr); 7057 /* 7058 This should work, but it doesn't 7059 sctx->ctx = ctx; 7060 mexMakeArrayPersistent(sctx->ctx); 7061 */ 7062 sctx->ctx = mxDuplicateArray(ctx); 7063 7064 ierr = TSSetIJacobian(ts,A,B,TSComputeJacobian_Matlab,sctx);CHKERRQ(ierr); 7065 PetscFunctionReturn(0); 7066 } 7067 7068 /* 7069 TSMonitor_Matlab - Calls the function that has been set with TSMonitorSetMatlab(). 7070 7071 Collective on TS 7072 7073 .seealso: TSSetFunction(), TSGetFunction() 7074 @*/ 7075 PetscErrorCode TSMonitor_Matlab(TS ts,PetscInt it, PetscReal time,Vec u, void *ctx) 7076 { 7077 PetscErrorCode ierr; 7078 TSMatlabContext *sctx = (TSMatlabContext*)ctx; 7079 int nlhs = 1,nrhs = 6; 7080 mxArray *plhs[1],*prhs[6]; 7081 long long int lx = 0,ls = 0; 7082 7083 PetscFunctionBegin; 7084 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 7085 PetscValidHeaderSpecific(u,VEC_CLASSID,4); 7086 7087 ierr = PetscMemcpy(&ls,&ts,sizeof(ts));CHKERRQ(ierr); 7088 ierr = PetscMemcpy(&lx,&u,sizeof(u));CHKERRQ(ierr); 7089 7090 prhs[0] = mxCreateDoubleScalar((double)ls); 7091 prhs[1] = mxCreateDoubleScalar((double)it); 7092 prhs[2] = mxCreateDoubleScalar((double)time); 7093 prhs[3] = mxCreateDoubleScalar((double)lx); 7094 prhs[4] = mxCreateString(sctx->funcname); 7095 prhs[5] = sctx->ctx; 7096 ierr = mexCallMATLAB(nlhs,plhs,nrhs,prhs,"PetscTSMonitorInternal");CHKERRQ(ierr); 7097 ierr = mxGetScalar(plhs[0]);CHKERRQ(ierr); 7098 mxDestroyArray(prhs[0]); 7099 mxDestroyArray(prhs[1]); 7100 mxDestroyArray(prhs[2]); 7101 mxDestroyArray(prhs[3]); 7102 mxDestroyArray(prhs[4]); 7103 mxDestroyArray(plhs[0]); 7104 PetscFunctionReturn(0); 7105 } 7106 7107 /* 7108 TSMonitorSetMatlab - Sets the monitor function from Matlab 7109 7110 Level: developer 7111 7112 .keywords: TS, nonlinear, set, function 7113 7114 .seealso: TSGetFunction(), TSComputeFunction(), TSSetJacobian(), TSSetFunction() 7115 */ 7116 PetscErrorCode TSMonitorSetMatlab(TS ts,const char *func,mxArray *ctx) 7117 { 7118 PetscErrorCode ierr; 7119 TSMatlabContext *sctx; 7120 7121 PetscFunctionBegin; 7122 /* currently sctx is memory bleed */ 7123 ierr = PetscNew(&sctx);CHKERRQ(ierr); 7124 ierr = PetscStrallocpy(func,&sctx->funcname);CHKERRQ(ierr); 7125 /* 7126 This should work, but it doesn't 7127 sctx->ctx = ctx; 7128 mexMakeArrayPersistent(sctx->ctx); 7129 */ 7130 sctx->ctx = mxDuplicateArray(ctx); 7131 7132 ierr = TSMonitorSet(ts,TSMonitor_Matlab,sctx,NULL);CHKERRQ(ierr); 7133 PetscFunctionReturn(0); 7134 } 7135 #endif 7136 7137 /*@C 7138 TSMonitorLGSolution - Monitors progress of the TS solvers by plotting each component of the solution vector 7139 in a time based line graph 7140 7141 Collective on TS 7142 7143 Input Parameters: 7144 + ts - the TS context 7145 . step - current time-step 7146 . ptime - current time 7147 . u - current solution 7148 - dctx - the TSMonitorLGCtx object that contains all the options for the monitoring, this is created with TSMonitorLGCtxCreate() 7149 7150 Options Database: 7151 . -ts_monitor_lg_solution_variables 7152 7153 Level: intermediate 7154 7155 Notes: Each process in a parallel run displays its component solutions in a separate window 7156 7157 .keywords: TS, vector, monitor, view 7158 7159 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGCtxCreate(), TSMonitorLGCtxSetVariableNames(), TSMonitorLGCtxGetVariableNames(), 7160 TSMonitorLGSetVariableNames(), TSMonitorLGGetVariableNames(), TSMonitorLGSetDisplayVariables(), TSMonitorLGCtxSetDisplayVariables(), 7161 TSMonitorLGCtxSetTransform(), TSMonitorLGSetTransform(), TSMonitorLGError(), TSMonitorLGSNESIterations(), TSMonitorLGKSPIterations(), 7162 TSMonitorEnvelopeCtxCreate(), TSMonitorEnvelopeGetBounds(), TSMonitorEnvelopeCtxDestroy(), TSMonitorEnvelop() 7163 @*/ 7164 PetscErrorCode TSMonitorLGSolution(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dctx) 7165 { 7166 PetscErrorCode ierr; 7167 TSMonitorLGCtx ctx = (TSMonitorLGCtx)dctx; 7168 const PetscScalar *yy; 7169 Vec v; 7170 7171 PetscFunctionBegin; 7172 if (step < 0) PetscFunctionReturn(0); /* -1 indicates interpolated solution */ 7173 if (!step) { 7174 PetscDrawAxis axis; 7175 PetscInt dim; 7176 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 7177 ierr = PetscDrawAxisSetLabels(axis,"Solution as function of time","Time","Solution");CHKERRQ(ierr); 7178 if (!ctx->names) { 7179 PetscBool flg; 7180 /* user provides names of variables to plot but no names has been set so assume names are integer values */ 7181 ierr = PetscOptionsHasName(((PetscObject)ts)->options,((PetscObject)ts)->prefix,"-ts_monitor_lg_solution_variables",&flg);CHKERRQ(ierr); 7182 if (flg) { 7183 PetscInt i,n; 7184 char **names; 7185 ierr = VecGetSize(u,&n);CHKERRQ(ierr); 7186 ierr = PetscMalloc1(n+1,&names);CHKERRQ(ierr); 7187 for (i=0; i<n; i++) { 7188 ierr = PetscMalloc1(5,&names[i]);CHKERRQ(ierr); 7189 ierr = PetscSNPrintf(names[i],5,"%D",i);CHKERRQ(ierr); 7190 } 7191 names[n] = NULL; 7192 ctx->names = names; 7193 } 7194 } 7195 if (ctx->names && !ctx->displaynames) { 7196 char **displaynames; 7197 PetscBool flg; 7198 ierr = VecGetLocalSize(u,&dim);CHKERRQ(ierr); 7199 ierr = PetscMalloc1(dim+1,&displaynames);CHKERRQ(ierr); 7200 ierr = PetscMemzero(displaynames,(dim+1)*sizeof(char*));CHKERRQ(ierr); 7201 ierr = PetscOptionsGetStringArray(((PetscObject)ts)->options,((PetscObject)ts)->prefix,"-ts_monitor_lg_solution_variables",displaynames,&dim,&flg);CHKERRQ(ierr); 7202 if (flg) { 7203 ierr = TSMonitorLGCtxSetDisplayVariables(ctx,(const char *const *)displaynames);CHKERRQ(ierr); 7204 } 7205 ierr = PetscStrArrayDestroy(&displaynames);CHKERRQ(ierr); 7206 } 7207 if (ctx->displaynames) { 7208 ierr = PetscDrawLGSetDimension(ctx->lg,ctx->ndisplayvariables);CHKERRQ(ierr); 7209 ierr = PetscDrawLGSetLegend(ctx->lg,(const char *const *)ctx->displaynames);CHKERRQ(ierr); 7210 } else if (ctx->names) { 7211 ierr = VecGetLocalSize(u,&dim);CHKERRQ(ierr); 7212 ierr = PetscDrawLGSetDimension(ctx->lg,dim);CHKERRQ(ierr); 7213 ierr = PetscDrawLGSetLegend(ctx->lg,(const char *const *)ctx->names);CHKERRQ(ierr); 7214 } else { 7215 ierr = VecGetLocalSize(u,&dim);CHKERRQ(ierr); 7216 ierr = PetscDrawLGSetDimension(ctx->lg,dim);CHKERRQ(ierr); 7217 } 7218 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 7219 } 7220 7221 if (!ctx->transform) v = u; 7222 else {ierr = (*ctx->transform)(ctx->transformctx,u,&v);CHKERRQ(ierr);} 7223 ierr = VecGetArrayRead(v,&yy);CHKERRQ(ierr); 7224 if (ctx->displaynames) { 7225 PetscInt i; 7226 for (i=0; i<ctx->ndisplayvariables; i++) 7227 ctx->displayvalues[i] = PetscRealPart(yy[ctx->displayvariables[i]]); 7228 ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,ctx->displayvalues);CHKERRQ(ierr); 7229 } else { 7230 #if defined(PETSC_USE_COMPLEX) 7231 PetscInt i,n; 7232 PetscReal *yreal; 7233 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 7234 ierr = PetscMalloc1(n,&yreal);CHKERRQ(ierr); 7235 for (i=0; i<n; i++) yreal[i] = PetscRealPart(yy[i]); 7236 ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,yreal);CHKERRQ(ierr); 7237 ierr = PetscFree(yreal);CHKERRQ(ierr); 7238 #else 7239 ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,yy);CHKERRQ(ierr); 7240 #endif 7241 } 7242 ierr = VecRestoreArrayRead(v,&yy);CHKERRQ(ierr); 7243 if (ctx->transform) {ierr = VecDestroy(&v);CHKERRQ(ierr);} 7244 7245 if (((ctx->howoften > 0) && (!(step % ctx->howoften))) || ((ctx->howoften == -1) && ts->reason)) { 7246 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 7247 ierr = PetscDrawLGSave(ctx->lg);CHKERRQ(ierr); 7248 } 7249 PetscFunctionReturn(0); 7250 } 7251 7252 /*@C 7253 TSMonitorLGSetVariableNames - Sets the name of each component in the solution vector so that it may be displayed in the plot 7254 7255 Collective on TS 7256 7257 Input Parameters: 7258 + ts - the TS context 7259 - names - the names of the components, final string must be NULL 7260 7261 Level: intermediate 7262 7263 Notes: If the TS object does not have a TSMonitorLGCtx associated with it then this function is ignored 7264 7265 .keywords: TS, vector, monitor, view 7266 7267 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetDisplayVariables(), TSMonitorLGCtxSetVariableNames() 7268 @*/ 7269 PetscErrorCode TSMonitorLGSetVariableNames(TS ts,const char * const *names) 7270 { 7271 PetscErrorCode ierr; 7272 PetscInt i; 7273 7274 PetscFunctionBegin; 7275 for (i=0; i<ts->numbermonitors; i++) { 7276 if (ts->monitor[i] == TSMonitorLGSolution) { 7277 ierr = TSMonitorLGCtxSetVariableNames((TSMonitorLGCtx)ts->monitorcontext[i],names);CHKERRQ(ierr); 7278 break; 7279 } 7280 } 7281 PetscFunctionReturn(0); 7282 } 7283 7284 /*@C 7285 TSMonitorLGCtxSetVariableNames - Sets the name of each component in the solution vector so that it may be displayed in the plot 7286 7287 Collective on TS 7288 7289 Input Parameters: 7290 + ts - the TS context 7291 - names - the names of the components, final string must be NULL 7292 7293 Level: intermediate 7294 7295 .keywords: TS, vector, monitor, view 7296 7297 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetDisplayVariables(), TSMonitorLGSetVariableNames() 7298 @*/ 7299 PetscErrorCode TSMonitorLGCtxSetVariableNames(TSMonitorLGCtx ctx,const char * const *names) 7300 { 7301 PetscErrorCode ierr; 7302 7303 PetscFunctionBegin; 7304 ierr = PetscStrArrayDestroy(&ctx->names);CHKERRQ(ierr); 7305 ierr = PetscStrArrayallocpy(names,&ctx->names);CHKERRQ(ierr); 7306 PetscFunctionReturn(0); 7307 } 7308 7309 /*@C 7310 TSMonitorLGGetVariableNames - Gets the name of each component in the solution vector so that it may be displayed in the plot 7311 7312 Collective on TS 7313 7314 Input Parameter: 7315 . ts - the TS context 7316 7317 Output Parameter: 7318 . names - the names of the components, final string must be NULL 7319 7320 Level: intermediate 7321 7322 Notes: If the TS object does not have a TSMonitorLGCtx associated with it then this function is ignored 7323 7324 .keywords: TS, vector, monitor, view 7325 7326 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetDisplayVariables() 7327 @*/ 7328 PetscErrorCode TSMonitorLGGetVariableNames(TS ts,const char *const **names) 7329 { 7330 PetscInt i; 7331 7332 PetscFunctionBegin; 7333 *names = NULL; 7334 for (i=0; i<ts->numbermonitors; i++) { 7335 if (ts->monitor[i] == TSMonitorLGSolution) { 7336 TSMonitorLGCtx ctx = (TSMonitorLGCtx) ts->monitorcontext[i]; 7337 *names = (const char *const *)ctx->names; 7338 break; 7339 } 7340 } 7341 PetscFunctionReturn(0); 7342 } 7343 7344 /*@C 7345 TSMonitorLGCtxSetDisplayVariables - Sets the variables that are to be display in the monitor 7346 7347 Collective on TS 7348 7349 Input Parameters: 7350 + ctx - the TSMonitorLG context 7351 . displaynames - the names of the components, final string must be NULL 7352 7353 Level: intermediate 7354 7355 .keywords: TS, vector, monitor, view 7356 7357 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetVariableNames() 7358 @*/ 7359 PetscErrorCode TSMonitorLGCtxSetDisplayVariables(TSMonitorLGCtx ctx,const char * const *displaynames) 7360 { 7361 PetscInt j = 0,k; 7362 PetscErrorCode ierr; 7363 7364 PetscFunctionBegin; 7365 if (!ctx->names) PetscFunctionReturn(0); 7366 ierr = PetscStrArrayDestroy(&ctx->displaynames);CHKERRQ(ierr); 7367 ierr = PetscStrArrayallocpy(displaynames,&ctx->displaynames);CHKERRQ(ierr); 7368 while (displaynames[j]) j++; 7369 ctx->ndisplayvariables = j; 7370 ierr = PetscMalloc1(ctx->ndisplayvariables,&ctx->displayvariables);CHKERRQ(ierr); 7371 ierr = PetscMalloc1(ctx->ndisplayvariables,&ctx->displayvalues);CHKERRQ(ierr); 7372 j = 0; 7373 while (displaynames[j]) { 7374 k = 0; 7375 while (ctx->names[k]) { 7376 PetscBool flg; 7377 ierr = PetscStrcmp(displaynames[j],ctx->names[k],&flg);CHKERRQ(ierr); 7378 if (flg) { 7379 ctx->displayvariables[j] = k; 7380 break; 7381 } 7382 k++; 7383 } 7384 j++; 7385 } 7386 PetscFunctionReturn(0); 7387 } 7388 7389 /*@C 7390 TSMonitorLGSetDisplayVariables - Sets the variables that are to be display in the monitor 7391 7392 Collective on TS 7393 7394 Input Parameters: 7395 + ts - the TS context 7396 . displaynames - the names of the components, final string must be NULL 7397 7398 Notes: If the TS object does not have a TSMonitorLGCtx associated with it then this function is ignored 7399 7400 Level: intermediate 7401 7402 .keywords: TS, vector, monitor, view 7403 7404 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetVariableNames() 7405 @*/ 7406 PetscErrorCode TSMonitorLGSetDisplayVariables(TS ts,const char * const *displaynames) 7407 { 7408 PetscInt i; 7409 PetscErrorCode ierr; 7410 7411 PetscFunctionBegin; 7412 for (i=0; i<ts->numbermonitors; i++) { 7413 if (ts->monitor[i] == TSMonitorLGSolution) { 7414 ierr = TSMonitorLGCtxSetDisplayVariables((TSMonitorLGCtx)ts->monitorcontext[i],displaynames);CHKERRQ(ierr); 7415 break; 7416 } 7417 } 7418 PetscFunctionReturn(0); 7419 } 7420 7421 /*@C 7422 TSMonitorLGSetTransform - Solution vector will be transformed by provided function before being displayed 7423 7424 Collective on TS 7425 7426 Input Parameters: 7427 + ts - the TS context 7428 . transform - the transform function 7429 . destroy - function to destroy the optional context 7430 - ctx - optional context used by transform function 7431 7432 Notes: If the TS object does not have a TSMonitorLGCtx associated with it then this function is ignored 7433 7434 Level: intermediate 7435 7436 .keywords: TS, vector, monitor, view 7437 7438 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetVariableNames(), TSMonitorLGCtxSetTransform() 7439 @*/ 7440 PetscErrorCode TSMonitorLGSetTransform(TS ts,PetscErrorCode (*transform)(void*,Vec,Vec*),PetscErrorCode (*destroy)(void*),void *tctx) 7441 { 7442 PetscInt i; 7443 PetscErrorCode ierr; 7444 7445 PetscFunctionBegin; 7446 for (i=0; i<ts->numbermonitors; i++) { 7447 if (ts->monitor[i] == TSMonitorLGSolution) { 7448 ierr = TSMonitorLGCtxSetTransform((TSMonitorLGCtx)ts->monitorcontext[i],transform,destroy,tctx);CHKERRQ(ierr); 7449 } 7450 } 7451 PetscFunctionReturn(0); 7452 } 7453 7454 /*@C 7455 TSMonitorLGCtxSetTransform - Solution vector will be transformed by provided function before being displayed 7456 7457 Collective on TSLGCtx 7458 7459 Input Parameters: 7460 + ts - the TS context 7461 . transform - the transform function 7462 . destroy - function to destroy the optional context 7463 - ctx - optional context used by transform function 7464 7465 Level: intermediate 7466 7467 .keywords: TS, vector, monitor, view 7468 7469 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetVariableNames(), TSMonitorLGSetTransform() 7470 @*/ 7471 PetscErrorCode TSMonitorLGCtxSetTransform(TSMonitorLGCtx ctx,PetscErrorCode (*transform)(void*,Vec,Vec*),PetscErrorCode (*destroy)(void*),void *tctx) 7472 { 7473 PetscFunctionBegin; 7474 ctx->transform = transform; 7475 ctx->transformdestroy = destroy; 7476 ctx->transformctx = tctx; 7477 PetscFunctionReturn(0); 7478 } 7479 7480 /*@C 7481 TSMonitorLGError - Monitors progress of the TS solvers by plotting each component of the error 7482 in a time based line graph 7483 7484 Collective on TS 7485 7486 Input Parameters: 7487 + ts - the TS context 7488 . step - current time-step 7489 . ptime - current time 7490 . u - current solution 7491 - dctx - TSMonitorLGCtx object created with TSMonitorLGCtxCreate() 7492 7493 Level: intermediate 7494 7495 Notes: Each process in a parallel run displays its component errors in a separate window 7496 7497 The user must provide the solution using TSSetSolutionFunction() to use this monitor. 7498 7499 Options Database Keys: 7500 . -ts_monitor_lg_error - create a graphical monitor of error history 7501 7502 .keywords: TS, vector, monitor, view 7503 7504 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSSetSolutionFunction() 7505 @*/ 7506 PetscErrorCode TSMonitorLGError(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy) 7507 { 7508 PetscErrorCode ierr; 7509 TSMonitorLGCtx ctx = (TSMonitorLGCtx)dummy; 7510 const PetscScalar *yy; 7511 Vec y; 7512 7513 PetscFunctionBegin; 7514 if (!step) { 7515 PetscDrawAxis axis; 7516 PetscInt dim; 7517 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 7518 ierr = PetscDrawAxisSetLabels(axis,"Error in solution as function of time","Time","Error");CHKERRQ(ierr); 7519 ierr = VecGetLocalSize(u,&dim);CHKERRQ(ierr); 7520 ierr = PetscDrawLGSetDimension(ctx->lg,dim);CHKERRQ(ierr); 7521 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 7522 } 7523 ierr = VecDuplicate(u,&y);CHKERRQ(ierr); 7524 ierr = TSComputeSolutionFunction(ts,ptime,y);CHKERRQ(ierr); 7525 ierr = VecAXPY(y,-1.0,u);CHKERRQ(ierr); 7526 ierr = VecGetArrayRead(y,&yy);CHKERRQ(ierr); 7527 #if defined(PETSC_USE_COMPLEX) 7528 { 7529 PetscReal *yreal; 7530 PetscInt i,n; 7531 ierr = VecGetLocalSize(y,&n);CHKERRQ(ierr); 7532 ierr = PetscMalloc1(n,&yreal);CHKERRQ(ierr); 7533 for (i=0; i<n; i++) yreal[i] = PetscRealPart(yy[i]); 7534 ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,yreal);CHKERRQ(ierr); 7535 ierr = PetscFree(yreal);CHKERRQ(ierr); 7536 } 7537 #else 7538 ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,yy);CHKERRQ(ierr); 7539 #endif 7540 ierr = VecRestoreArrayRead(y,&yy);CHKERRQ(ierr); 7541 ierr = VecDestroy(&y);CHKERRQ(ierr); 7542 if (((ctx->howoften > 0) && (!(step % ctx->howoften))) || ((ctx->howoften == -1) && ts->reason)) { 7543 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 7544 ierr = PetscDrawLGSave(ctx->lg);CHKERRQ(ierr); 7545 } 7546 PetscFunctionReturn(0); 7547 } 7548 7549 PetscErrorCode TSMonitorLGSNESIterations(TS ts,PetscInt n,PetscReal ptime,Vec v,void *monctx) 7550 { 7551 TSMonitorLGCtx ctx = (TSMonitorLGCtx) monctx; 7552 PetscReal x = ptime,y; 7553 PetscErrorCode ierr; 7554 PetscInt its; 7555 7556 PetscFunctionBegin; 7557 if (n < 0) PetscFunctionReturn(0); /* -1 indicates interpolated solution */ 7558 if (!n) { 7559 PetscDrawAxis axis; 7560 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 7561 ierr = PetscDrawAxisSetLabels(axis,"Nonlinear iterations as function of time","Time","SNES Iterations");CHKERRQ(ierr); 7562 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 7563 ctx->snes_its = 0; 7564 } 7565 ierr = TSGetSNESIterations(ts,&its);CHKERRQ(ierr); 7566 y = its - ctx->snes_its; 7567 ierr = PetscDrawLGAddPoint(ctx->lg,&x,&y);CHKERRQ(ierr); 7568 if (((ctx->howoften > 0) && (!(n % ctx->howoften)) && (n > -1)) || ((ctx->howoften == -1) && (n == -1))) { 7569 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 7570 ierr = PetscDrawLGSave(ctx->lg);CHKERRQ(ierr); 7571 } 7572 ctx->snes_its = its; 7573 PetscFunctionReturn(0); 7574 } 7575 7576 PetscErrorCode TSMonitorLGKSPIterations(TS ts,PetscInt n,PetscReal ptime,Vec v,void *monctx) 7577 { 7578 TSMonitorLGCtx ctx = (TSMonitorLGCtx) monctx; 7579 PetscReal x = ptime,y; 7580 PetscErrorCode ierr; 7581 PetscInt its; 7582 7583 PetscFunctionBegin; 7584 if (n < 0) PetscFunctionReturn(0); /* -1 indicates interpolated solution */ 7585 if (!n) { 7586 PetscDrawAxis axis; 7587 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 7588 ierr = PetscDrawAxisSetLabels(axis,"Linear iterations as function of time","Time","KSP Iterations");CHKERRQ(ierr); 7589 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 7590 ctx->ksp_its = 0; 7591 } 7592 ierr = TSGetKSPIterations(ts,&its);CHKERRQ(ierr); 7593 y = its - ctx->ksp_its; 7594 ierr = PetscDrawLGAddPoint(ctx->lg,&x,&y);CHKERRQ(ierr); 7595 if (((ctx->howoften > 0) && (!(n % ctx->howoften)) && (n > -1)) || ((ctx->howoften == -1) && (n == -1))) { 7596 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 7597 ierr = PetscDrawLGSave(ctx->lg);CHKERRQ(ierr); 7598 } 7599 ctx->ksp_its = its; 7600 PetscFunctionReturn(0); 7601 } 7602 7603 /*@ 7604 TSComputeLinearStability - computes the linear stability function at a point 7605 7606 Collective on TS and Vec 7607 7608 Input Parameters: 7609 + ts - the TS context 7610 - xr,xi - real and imaginary part of input arguments 7611 7612 Output Parameters: 7613 . yr,yi - real and imaginary part of function value 7614 7615 Level: developer 7616 7617 .keywords: TS, compute 7618 7619 .seealso: TSSetRHSFunction(), TSComputeIFunction() 7620 @*/ 7621 PetscErrorCode TSComputeLinearStability(TS ts,PetscReal xr,PetscReal xi,PetscReal *yr,PetscReal *yi) 7622 { 7623 PetscErrorCode ierr; 7624 7625 PetscFunctionBegin; 7626 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 7627 if (!ts->ops->linearstability) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Linearized stability function not provided for this method"); 7628 ierr = (*ts->ops->linearstability)(ts,xr,xi,yr,yi);CHKERRQ(ierr); 7629 PetscFunctionReturn(0); 7630 } 7631 7632 /* ------------------------------------------------------------------------*/ 7633 /*@C 7634 TSMonitorEnvelopeCtxCreate - Creates a context for use with TSMonitorEnvelope() 7635 7636 Collective on TS 7637 7638 Input Parameters: 7639 . ts - the ODE solver object 7640 7641 Output Parameter: 7642 . ctx - the context 7643 7644 Level: intermediate 7645 7646 .keywords: TS, monitor, line graph, residual, seealso 7647 7648 .seealso: TSMonitorLGTimeStep(), TSMonitorSet(), TSMonitorLGSolution(), TSMonitorLGError() 7649 7650 @*/ 7651 PetscErrorCode TSMonitorEnvelopeCtxCreate(TS ts,TSMonitorEnvelopeCtx *ctx) 7652 { 7653 PetscErrorCode ierr; 7654 7655 PetscFunctionBegin; 7656 ierr = PetscNew(ctx);CHKERRQ(ierr); 7657 PetscFunctionReturn(0); 7658 } 7659 7660 /*@C 7661 TSMonitorEnvelope - Monitors the maximum and minimum value of each component of the solution 7662 7663 Collective on TS 7664 7665 Input Parameters: 7666 + ts - the TS context 7667 . step - current time-step 7668 . ptime - current time 7669 . u - current solution 7670 - dctx - the envelope context 7671 7672 Options Database: 7673 . -ts_monitor_envelope 7674 7675 Level: intermediate 7676 7677 Notes: after a solve you can use TSMonitorEnvelopeGetBounds() to access the envelope 7678 7679 .keywords: TS, vector, monitor, view 7680 7681 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorEnvelopeGetBounds(), TSMonitorEnvelopeCtxCreate() 7682 @*/ 7683 PetscErrorCode TSMonitorEnvelope(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dctx) 7684 { 7685 PetscErrorCode ierr; 7686 TSMonitorEnvelopeCtx ctx = (TSMonitorEnvelopeCtx)dctx; 7687 7688 PetscFunctionBegin; 7689 if (!ctx->max) { 7690 ierr = VecDuplicate(u,&ctx->max);CHKERRQ(ierr); 7691 ierr = VecDuplicate(u,&ctx->min);CHKERRQ(ierr); 7692 ierr = VecCopy(u,ctx->max);CHKERRQ(ierr); 7693 ierr = VecCopy(u,ctx->min);CHKERRQ(ierr); 7694 } else { 7695 ierr = VecPointwiseMax(ctx->max,u,ctx->max);CHKERRQ(ierr); 7696 ierr = VecPointwiseMin(ctx->min,u,ctx->min);CHKERRQ(ierr); 7697 } 7698 PetscFunctionReturn(0); 7699 } 7700 7701 /*@C 7702 TSMonitorEnvelopeGetBounds - Gets the bounds for the components of the solution 7703 7704 Collective on TS 7705 7706 Input Parameter: 7707 . ts - the TS context 7708 7709 Output Parameter: 7710 + max - the maximum values 7711 - min - the minimum values 7712 7713 Notes: If the TS does not have a TSMonitorEnvelopeCtx associated with it then this function is ignored 7714 7715 Level: intermediate 7716 7717 .keywords: TS, vector, monitor, view 7718 7719 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetDisplayVariables() 7720 @*/ 7721 PetscErrorCode TSMonitorEnvelopeGetBounds(TS ts,Vec *max,Vec *min) 7722 { 7723 PetscInt i; 7724 7725 PetscFunctionBegin; 7726 if (max) *max = NULL; 7727 if (min) *min = NULL; 7728 for (i=0; i<ts->numbermonitors; i++) { 7729 if (ts->monitor[i] == TSMonitorEnvelope) { 7730 TSMonitorEnvelopeCtx ctx = (TSMonitorEnvelopeCtx) ts->monitorcontext[i]; 7731 if (max) *max = ctx->max; 7732 if (min) *min = ctx->min; 7733 break; 7734 } 7735 } 7736 PetscFunctionReturn(0); 7737 } 7738 7739 /*@C 7740 TSMonitorEnvelopeCtxDestroy - Destroys a context that was created with TSMonitorEnvelopeCtxCreate(). 7741 7742 Collective on TSMonitorEnvelopeCtx 7743 7744 Input Parameter: 7745 . ctx - the monitor context 7746 7747 Level: intermediate 7748 7749 .keywords: TS, monitor, line graph, destroy 7750 7751 .seealso: TSMonitorLGCtxCreate(), TSMonitorSet(), TSMonitorLGTimeStep() 7752 @*/ 7753 PetscErrorCode TSMonitorEnvelopeCtxDestroy(TSMonitorEnvelopeCtx *ctx) 7754 { 7755 PetscErrorCode ierr; 7756 7757 PetscFunctionBegin; 7758 ierr = VecDestroy(&(*ctx)->min);CHKERRQ(ierr); 7759 ierr = VecDestroy(&(*ctx)->max);CHKERRQ(ierr); 7760 ierr = PetscFree(*ctx);CHKERRQ(ierr); 7761 PetscFunctionReturn(0); 7762 } 7763 7764 /*@ 7765 TSRestartStep - Flags the solver to restart the next step 7766 7767 Collective on TS 7768 7769 Input Parameter: 7770 . ts - the TS context obtained from TSCreate() 7771 7772 Level: advanced 7773 7774 Notes: 7775 Multistep methods like BDF or Runge-Kutta methods with FSAL property require restarting the solver in the event of 7776 discontinuities. These discontinuities may be introduced as a consequence of explicitly modifications to the solution 7777 vector (which PETSc attempts to detect and handle) or problem coefficients (which PETSc is not able to detect). For 7778 the sake of correctness and maximum safety, users are expected to call TSRestart() whenever they introduce 7779 discontinuities in callback routines (e.g. prestep and poststep routines, or implicit/rhs function routines with 7780 discontinuous source terms). 7781 7782 .keywords: TS, timestep, restart 7783 7784 .seealso: TSSolve(), TSSetPreStep(), TSSetPostStep() 7785 @*/ 7786 PetscErrorCode TSRestartStep(TS ts) 7787 { 7788 PetscFunctionBegin; 7789 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 7790 ts->steprestart = PETSC_TRUE; 7791 PetscFunctionReturn(0); 7792 } 7793 7794 /*@ 7795 TSRollBack - Rolls back one time step 7796 7797 Collective on TS 7798 7799 Input Parameter: 7800 . ts - the TS context obtained from TSCreate() 7801 7802 Level: advanced 7803 7804 .keywords: TS, timestep, rollback 7805 7806 .seealso: TSCreate(), TSSetUp(), TSDestroy(), TSSolve(), TSSetPreStep(), TSSetPreStage(), TSInterpolate() 7807 @*/ 7808 PetscErrorCode TSRollBack(TS ts) 7809 { 7810 PetscErrorCode ierr; 7811 7812 PetscFunctionBegin; 7813 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 7814 if (ts->steprollback) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONGSTATE,"TSRollBack already called"); 7815 if (!ts->ops->rollback) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"TSRollBack not implemented for type '%s'",((PetscObject)ts)->type_name); 7816 ierr = (*ts->ops->rollback)(ts);CHKERRQ(ierr); 7817 ts->time_step = ts->ptime - ts->ptime_prev; 7818 ts->ptime = ts->ptime_prev; 7819 ts->ptime_prev = ts->ptime_prev_rollback; 7820 ts->steps--; 7821 ts->steprollback = PETSC_TRUE; 7822 PetscFunctionReturn(0); 7823 } 7824 7825 /*@ 7826 TSGetStages - Get the number of stages and stage values 7827 7828 Input Parameter: 7829 . ts - the TS context obtained from TSCreate() 7830 7831 Level: advanced 7832 7833 .keywords: TS, getstages 7834 7835 .seealso: TSCreate() 7836 @*/ 7837 PetscErrorCode TSGetStages(TS ts,PetscInt *ns,Vec **Y) 7838 { 7839 PetscErrorCode ierr; 7840 7841 PetscFunctionBegin; 7842 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 7843 PetscValidPointer(ns,2); 7844 7845 if (!ts->ops->getstages) *ns=0; 7846 else { 7847 ierr = (*ts->ops->getstages)(ts,ns,Y);CHKERRQ(ierr); 7848 } 7849 PetscFunctionReturn(0); 7850 } 7851 7852 /*@C 7853 TSComputeIJacobianDefaultColor - Computes the Jacobian using finite differences and coloring to exploit matrix sparsity. 7854 7855 Collective on SNES 7856 7857 Input Parameters: 7858 + ts - the TS context 7859 . t - current timestep 7860 . U - state vector 7861 . Udot - time derivative of state vector 7862 . shift - shift to apply, see note below 7863 - ctx - an optional user context 7864 7865 Output Parameters: 7866 + J - Jacobian matrix (not altered in this routine) 7867 - B - newly computed Jacobian matrix to use with preconditioner (generally the same as J) 7868 7869 Level: intermediate 7870 7871 Notes: 7872 If F(t,U,Udot)=0 is the DAE, the required Jacobian is 7873 7874 dF/dU + shift*dF/dUdot 7875 7876 Most users should not need to explicitly call this routine, as it 7877 is used internally within the nonlinear solvers. 7878 7879 This will first try to get the coloring from the DM. If the DM type has no coloring 7880 routine, then it will try to get the coloring from the matrix. This requires that the 7881 matrix have nonzero entries precomputed. 7882 7883 .keywords: TS, finite differences, Jacobian, coloring, sparse 7884 .seealso: TSSetIJacobian(), MatFDColoringCreate(), MatFDColoringSetFunction() 7885 @*/ 7886 PetscErrorCode TSComputeIJacobianDefaultColor(TS ts,PetscReal t,Vec U,Vec Udot,PetscReal shift,Mat J,Mat B,void *ctx) 7887 { 7888 SNES snes; 7889 MatFDColoring color; 7890 PetscBool hascolor, matcolor = PETSC_FALSE; 7891 PetscErrorCode ierr; 7892 7893 PetscFunctionBegin; 7894 ierr = PetscOptionsGetBool(((PetscObject)ts)->options,((PetscObject) ts)->prefix, "-ts_fd_color_use_mat", &matcolor, NULL);CHKERRQ(ierr); 7895 ierr = PetscObjectQuery((PetscObject) B, "TSMatFDColoring", (PetscObject *) &color);CHKERRQ(ierr); 7896 if (!color) { 7897 DM dm; 7898 ISColoring iscoloring; 7899 7900 ierr = TSGetDM(ts, &dm);CHKERRQ(ierr); 7901 ierr = DMHasColoring(dm, &hascolor);CHKERRQ(ierr); 7902 if (hascolor && !matcolor) { 7903 ierr = DMCreateColoring(dm, IS_COLORING_GLOBAL, &iscoloring);CHKERRQ(ierr); 7904 ierr = MatFDColoringCreate(B, iscoloring, &color);CHKERRQ(ierr); 7905 ierr = MatFDColoringSetFunction(color, (PetscErrorCode (*)(void)) SNESTSFormFunction, (void *) ts);CHKERRQ(ierr); 7906 ierr = MatFDColoringSetFromOptions(color);CHKERRQ(ierr); 7907 ierr = MatFDColoringSetUp(B, iscoloring, color);CHKERRQ(ierr); 7908 ierr = ISColoringDestroy(&iscoloring);CHKERRQ(ierr); 7909 } else { 7910 MatColoring mc; 7911 7912 ierr = MatColoringCreate(B, &mc);CHKERRQ(ierr); 7913 ierr = MatColoringSetDistance(mc, 2);CHKERRQ(ierr); 7914 ierr = MatColoringSetType(mc, MATCOLORINGSL);CHKERRQ(ierr); 7915 ierr = MatColoringSetFromOptions(mc);CHKERRQ(ierr); 7916 ierr = MatColoringApply(mc, &iscoloring);CHKERRQ(ierr); 7917 ierr = MatColoringDestroy(&mc);CHKERRQ(ierr); 7918 ierr = MatFDColoringCreate(B, iscoloring, &color);CHKERRQ(ierr); 7919 ierr = MatFDColoringSetFunction(color, (PetscErrorCode (*)(void)) SNESTSFormFunction, (void *) ts);CHKERRQ(ierr); 7920 ierr = MatFDColoringSetFromOptions(color);CHKERRQ(ierr); 7921 ierr = MatFDColoringSetUp(B, iscoloring, color);CHKERRQ(ierr); 7922 ierr = ISColoringDestroy(&iscoloring);CHKERRQ(ierr); 7923 } 7924 ierr = PetscObjectCompose((PetscObject) B, "TSMatFDColoring", (PetscObject) color);CHKERRQ(ierr); 7925 ierr = PetscObjectDereference((PetscObject) color);CHKERRQ(ierr); 7926 } 7927 ierr = TSGetSNES(ts, &snes);CHKERRQ(ierr); 7928 ierr = MatFDColoringApply(B, color, U, snes);CHKERRQ(ierr); 7929 if (J != B) { 7930 ierr = MatAssemblyBegin(J, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 7931 ierr = MatAssemblyEnd(J, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 7932 } 7933 PetscFunctionReturn(0); 7934 } 7935 7936 /*@ 7937 TSSetFunctionDomainError - Set the function testing if the current state vector is valid 7938 7939 Input Parameters: 7940 ts - the TS context 7941 func - function called within TSFunctionDomainError 7942 7943 Level: intermediate 7944 7945 .keywords: TS, state, domain 7946 .seealso: TSAdaptCheckStage(), TSFunctionDomainError() 7947 @*/ 7948 7949 PetscErrorCode TSSetFunctionDomainError(TS ts, PetscErrorCode (*func)(TS,PetscReal,Vec,PetscBool*)) 7950 { 7951 PetscFunctionBegin; 7952 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 7953 ts->functiondomainerror = func; 7954 PetscFunctionReturn(0); 7955 } 7956 7957 /*@ 7958 TSFunctionDomainError - Check if the current state is valid 7959 7960 Input Parameters: 7961 ts - the TS context 7962 stagetime - time of the simulation 7963 Y - state vector to check. 7964 7965 Output Parameter: 7966 accept - Set to PETSC_FALSE if the current state vector is valid. 7967 7968 Note: 7969 This function should be used to ensure the state is in a valid part of the space. 7970 For example, one can ensure here all values are positive. 7971 7972 Level: advanced 7973 @*/ 7974 PetscErrorCode TSFunctionDomainError(TS ts,PetscReal stagetime,Vec Y,PetscBool* accept) 7975 { 7976 PetscErrorCode ierr; 7977 7978 PetscFunctionBegin; 7979 7980 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 7981 *accept = PETSC_TRUE; 7982 if (ts->functiondomainerror) { 7983 PetscStackCallStandard((*ts->functiondomainerror),(ts,stagetime,Y,accept)); 7984 } 7985 PetscFunctionReturn(0); 7986 } 7987 7988 /*@C 7989 TSClone - This function clones a time step object. 7990 7991 Collective on MPI_Comm 7992 7993 Input Parameter: 7994 . tsin - The input TS 7995 7996 Output Parameter: 7997 . tsout - The output TS (cloned) 7998 7999 Notes: 8000 This function is used to create a clone of a TS object. It is used in ARKIMEX for initializing the slope for first stage explicit methods. It will likely be replaced in the future with a mechanism of switching methods on the fly. 8001 8002 When using TSDestroy() on a clone the user has to first reset the correct TS reference in the embedded SNES object: e.g.: by running SNES snes_dup=NULL; TSGetSNES(ts,&snes_dup); ierr = TSSetSNES(ts,snes_dup); 8003 8004 Level: developer 8005 8006 .keywords: TS, clone 8007 .seealso: TSCreate(), TSSetType(), TSSetUp(), TSDestroy(), TSSetProblemType() 8008 @*/ 8009 PetscErrorCode TSClone(TS tsin, TS *tsout) 8010 { 8011 TS t; 8012 PetscErrorCode ierr; 8013 SNES snes_start; 8014 DM dm; 8015 TSType type; 8016 8017 PetscFunctionBegin; 8018 PetscValidPointer(tsin,1); 8019 *tsout = NULL; 8020 8021 ierr = PetscHeaderCreate(t, TS_CLASSID, "TS", "Time stepping", "TS", PetscObjectComm((PetscObject)tsin), TSDestroy, TSView);CHKERRQ(ierr); 8022 8023 /* General TS description */ 8024 t->numbermonitors = 0; 8025 t->setupcalled = 0; 8026 t->ksp_its = 0; 8027 t->snes_its = 0; 8028 t->nwork = 0; 8029 t->rhsjacobian.time = -1e20; 8030 t->rhsjacobian.scale = 1.; 8031 t->ijacobian.shift = 1.; 8032 8033 ierr = TSGetSNES(tsin,&snes_start);CHKERRQ(ierr); 8034 ierr = TSSetSNES(t,snes_start);CHKERRQ(ierr); 8035 8036 ierr = TSGetDM(tsin,&dm);CHKERRQ(ierr); 8037 ierr = TSSetDM(t,dm);CHKERRQ(ierr); 8038 8039 t->adapt = tsin->adapt; 8040 ierr = PetscObjectReference((PetscObject)t->adapt);CHKERRQ(ierr); 8041 8042 t->trajectory = tsin->trajectory; 8043 ierr = PetscObjectReference((PetscObject)t->trajectory);CHKERRQ(ierr); 8044 8045 t->event = tsin->event; 8046 if (t->event) t->event->refct++; 8047 8048 t->problem_type = tsin->problem_type; 8049 t->ptime = tsin->ptime; 8050 t->ptime_prev = tsin->ptime_prev; 8051 t->time_step = tsin->time_step; 8052 t->max_time = tsin->max_time; 8053 t->steps = tsin->steps; 8054 t->max_steps = tsin->max_steps; 8055 t->equation_type = tsin->equation_type; 8056 t->atol = tsin->atol; 8057 t->rtol = tsin->rtol; 8058 t->max_snes_failures = tsin->max_snes_failures; 8059 t->max_reject = tsin->max_reject; 8060 t->errorifstepfailed = tsin->errorifstepfailed; 8061 8062 ierr = TSGetType(tsin,&type);CHKERRQ(ierr); 8063 ierr = TSSetType(t,type);CHKERRQ(ierr); 8064 8065 t->vec_sol = NULL; 8066 8067 t->cfltime = tsin->cfltime; 8068 t->cfltime_local = tsin->cfltime_local; 8069 t->exact_final_time = tsin->exact_final_time; 8070 8071 ierr = PetscMemcpy(t->ops,tsin->ops,sizeof(struct _TSOps));CHKERRQ(ierr); 8072 8073 if (((PetscObject)tsin)->fortran_func_pointers) { 8074 PetscInt i; 8075 ierr = PetscMalloc((10)*sizeof(void(*)(void)),&((PetscObject)t)->fortran_func_pointers);CHKERRQ(ierr); 8076 for (i=0; i<10; i++) { 8077 ((PetscObject)t)->fortran_func_pointers[i] = ((PetscObject)tsin)->fortran_func_pointers[i]; 8078 } 8079 } 8080 *tsout = t; 8081 PetscFunctionReturn(0); 8082 } 8083